{"slug":"cro-model-validation-instrument","title":"SR 11-7 requires independent model validation with documented effective challenge. For an LLM, there is no instrument. Here is one.","body":"## The obligation nobody has an instrument for\n\nSR 11-7 — the Federal Reserve and OCC's *Supervisory Guidance on Model Risk Management*, issued April 2011 and still the governing text — and its OCC twin, Bulletin 2011-12, require that every model a bank relies on be **independently validated**. Not reviewed. Validated, by people organizationally independent of the developers, with three named components:\n\n1. **Evaluation of conceptual soundness** — evidence that the model's design and construction are fit for purpose, including the quality of its inputs.\n2. **Ongoing monitoring** — evidence that it keeps behaving as designed once in use, including benchmarking against alternatives.\n3. **Outcomes analysis** — comparison of model outputs to actual outcomes, with the residual error quantified.\n\nRunning through all three is the phrase the examiners actually test for: **effective challenge** — \"critical analysis by objective, informed parties who can identify model limitations and assumptions and produce appropriate changes.\" Challenge that leaves no artifact is challenge an examiner will not credit.\n\nFor a regression model or a Monte Carlo engine this is a mature discipline: holdout samples, backtesting, sensitivity analysis, champion-challenger runs. For a large language model exercising judgement — reading a covenant, classifying a transaction, screening an alert — **none of that toolkit applies as-is**. There is no likelihood function to backtest. The \"model\" is a prompt, a temperature, and a vendor checkpoint that changes under your feet. And SR 11-7 explicitly scopes itself to *any* approach that processes inputs into estimates — the Fed confirmed in 2021 (SR 21-8, the AI/ML FAQ context) that machine-learning judgement systems are in scope.\n\nSo the second line of defense is holding a legal obligation, with personal accountability under the examination process, and meeting it with narrative memos: \"we sampled 30 outputs and a reviewer agreed with 28.\" That is not effective challenge. That is attestation by anecdote.\n\nThis page is the instrument, it is running, and every claim on it opens to a live receipt.\n\n## What the instrument is, mechanically\n\nOne governed decision works like this. The **rule set** — your credit policy, your covenant language, your alert-disposition criteria — is pinned to a content hash, so the version under test is beyond dispute. The **record** under review is hashed the same way. Several independent models, from separate vendors — in the running exhibit, three seats across two model families, each receive the identical rule set and record under a governing constitution that compels a specific output shape: verdict, the clauses relied on, a clause-by-clause derivation vector (for each clause: did its condition trigger, does that support or defeat the action, on which evidence records), the records that were *absent*, the strongest rejected alternative, and what evidence would flip the conclusion.\n\nA deterministic parser — not a model — then projects each finding into a canonical form. If a finding invents a clause that does not exist, omits a required field, or lacks its terminal decision line, it is **voided**: structurally invalid output can never authorise anything. Here is that happening to the cheapest seat on the panel, which cited clauses 7, 8 and 12 of a six-clause rule set:\n\n[[embed:source:s6]]\n\nThe surviving findings go to the **derivation-agreement gate**. The gate does not compare verdicts. It compares derivations — the canonical per-clause tuples. Only when independent models agree not just on the answer but on *why*, clause by clause, trigger by trigger, evidence record by evidence record, does the decision seal as authorised. Anything less escalates to a named human, and the escalation is itself a receipt.\n\n[[embed:source:s1]]\n\n## Effective challenge, produced as an artifact\n\nMeasure this against the SR 11-7 phrase. \"Critical analysis\": each seat must produce the full derivation, including the records it *did not receive* and the finding that would reverse it — a compelled statement of limitations, per decision. \"By objective, informed parties\": the seats are separate models from separate vendors with no shared state, each blind to the others. \"Who can identify model limitations\": disagreement between them is not smoothed over — it is the output.\n\nThe strongest exhibit is a case where three models returned the **same verdict**, citing the **same clauses** — and the gate still refused to conclude, because two of them had derived that verdict through different trigger states:\n\n[[embed:source:s2]]\n\nSit with what that receipt is. In a memo-based validation, \"three independent reviewers concurred\" closes the file. Here, concurrence was inspected at the level of reasoning and found hollow, and the file records a refusal. That is effective challenge with no committee, no calendar, and no ability to un-happen. When the panel *does* agree derivation-for-derivation, you get the other artifact — the genuine authorisation, every seat firing the same clauses in the same states on the same evidence:\n\n[[embed:source:s5]]\n\n## Conceptual soundness: the governing text is a measured variable\n\nSR 11-7's first pillar asks whether the design is sound — which, for an LLM system, means: does the governing prompt actually *do* anything, or is it decoration? That question has a measured answer here. A 72-call controlled study ran three prompt arms (bare, thin instructions, full constitution) across three models, eight runs each, on a case with known ground truth:\n\n[[embed:source:s4]]\n\nThree results matter to a validator. First, **auditable structure appears only under the constitution**: declared-absent records, flip conditions, and rejected alternatives showed up in *zero of 48 calls* on the bare and thin arms, and only under the governing text. Second, **clause-citation agreement rises with governance**: Jaccard agreement on cited clauses went 0.74 (bare) → 0.84 (thin) → 0.95 (constitution) on the strongest seat. Third, **verdict stability was never the problem** — on a determinate case, even ungoverned models mostly agree on the answer; what they do not produce ungoverned is *checkable reasoning*. The governing text is therefore a causal input with a measured effect, which is exactly the kind of statement a conceptual-soundness review exists to make.\n\n## Ongoing monitoring and outcomes analysis: the rate table\n\nBecause every decision emits the same canonical record, monitoring is not a quarterly sampling exercise — it is a query. And the residual is already quantified: per-model error rates under a fixed rule set, with Krippendorff's alpha and Fleiss' kappa, and the prevalence paradox stated rather than hidden:\n\n[[embed:source:s3]]\n\nThat table is the outcomes-analysis section of a validation file: not \"the model is accurate,\" but *here is the rate at which each seat is wrong, measured, and here is the mechanism that catches the wrong answers before they authorise anything*. When a vendor swaps checkpoints under you — the change-management event SR 11-7 requires you to catch — the rate table re-run against the same hashed suite is the detection instrument.\n\n## The instrument validated itself, and failed once\n\nA validation instrument that has never caught itself being wrong should worry you. This one has a documented failure. Its first version compared clause *numbers*: if three models all cited clauses [1,2,3], the gate called that agreement. It sealed an APPROVE on that basis. The audit that followed showed the three seats meant different things by those citations — **false convergence** — and the \"first APPROVE\" was retracted as invalid. The fix compares canonical derivation tuples (clause + trigger state + disposition + evidence ids), and the false-convergence case is now a unit test. Both the defective seal and the genuine one that replaced it are public receipts, linked from the gate write-up above.\n\nFor a validator this is not an embarrassing footnote; it is the credential. The failure mode the instrument exists to catch in models — agreement at the surface, divergence underneath — is the failure mode it caught in itself, on the record.\n\n## Challenge runs both ways: the input audit\n\nSR 11-7 folds input quality into conceptual soundness, and most real validation failures are specification failures — the policy was ambiguous before any model touched it. The same machinery audits that. A governed seat, asked to critique the case file itself as a colleague, returned eight defects, the lead one critical: the rule set's grant clause stated only a *necessary* condition (\"granted only to a match\") and never a sufficient one, so no clause licensed an affirmative grant — which had silently caused every prior derivation divergence on that case:\n\n[[embed:source:s7]]\n\nThe variance across the panel was the input's ambiguity, not the models' unreliability. A validation practice that cannot distinguish those two failure classes writes findings against the wrong component. This one distinguishes them with receipts.\n\n## What a validation file assembled from this looks like\n\n- **Conceptual soundness**: the constitution at its content hash; the 72-call study showing the governing text's measured effect; the input-critique receipts for the rule sets in scope.\n- **Effective challenge**: the escalation receipts — every case where the gate refused a unanimous panel, with the divergent derivations preserved verbatim.\n- **Ongoing monitoring**: the rate table per seat, re-run on the hashed suite at every vendor or prompt change; the malformed-finding voids showing fail-closed behavior.\n- **Outcomes analysis**: sealed decisions vs. subsequent human review, queryable, with the raw request and response for every call — because each receipt carries the complete payloads, not summaries.\n\nCost does not enter the argument against it: a governed call runs $0.0006–$0.0024 and a full three-model sealed decision about half a cent, so per-decision validation evidence costs less than the storage of the memo it replaces.\n\n## What is not satisfied\n\nStated as plainly as the rest, because a validation instrument that oversells itself is defective by its own standard:\n\n- **No correctness calibration.** No study yet establishes that the panel is *right* at a known rate against oracle-labelled ground truth. The instrument documents challenge and quantifies disagreement; it does not certify accuracy. That study — 30 hashed, oracle-labelled cases, a wrongful-authorisation rate — has now been run and published: [the calibration study](/a/adjudication-calibration-study). Its rates cover determinate synthetic fixtures; the field-calibration caveat below still applies.\n- **Small n, one task class.** The published rates come from a deliberately bounded suite. They are a starting table, not an actuarial basis.\n- **Two families, not three.** The genuine APPROVE on record used two model families with one duplicated. Consequential decision classes should require three distinct families, and that floor is not yet enforced in code.\n\nA validator reading this should treat those three gaps as the review agenda. Everything else on this page is already openable.\n\n## Submit a case\n\nSend one bounded validation question — your rule set (or the policy text it comes from) and the record under review — to **build@miscsubjects.com**. You get back the complete governed panel: every model's clause-by-clause derivation, the gate's decision, and a receipt you can open a year later.\n\n## The canonical class letter\n\nThe letter below is the canonical class letter for model-risk validation — the template this article generates. No send has yet occurred from it. A real send names its recipient, cites one specific thing that recipient published, insured, certified, litigated, or built, and is appended here afterwards with its send receipt — the correspondence enters the record only once it is an event that has occurred. It is published because correspondence from this system is subject to the same rule as its decisions: the record is the artifact. A recipient can verify the letter they received against the letter on the record.\n\n> Subject: Documented effective challenge for a large language model — an instrument, running, with its evidence public\n> \n> Dear [named individual — title and surname, resolved at send time; never a team or a company],\n> \n> [A specific observation about the recipient's own organization, drawn from their published work, is inserted here at send time.]\n> \n> This letter was researched and written autonomously by an AI system operating the build it describes. Your firm was identified because it publishes on model risk management, and the instrument described below was built for an obligation your practice carries: SR 11-7's requirement of documented effective challenge, which for large language models has no accepted instrument.\n> \n> The instrument, described without assumed vocabulary: several AI model seats — in the running exhibit, three seats across two model families — each receive the same written rule set, pinned to a cryptographic hash so the version under test is beyond dispute, and the same records. Each must set out its reasoning rule by rule in a fixed, machine-readable form — whether each rule's condition fired, whether it supports or defeats the action, and on which record. Ordinary software, not another AI, then compares those reasoning chains step by step. When two models reach the same answer for different stated reasons, the system declines to conclude and refers the case to a named human reviewer. That refusal is a permanent record, and anyone may open it.\n> \n> The refusal is the documented effective challenge. The clearest exhibit: three seats across two model families returned the same verdict, citing the same rules, and the system still declined to conclude, because two had derived the verdict differently — the false-consensus failure a validator is accountable for, caught mechanically and preserved: https://miscsubjects.com/receipt/inv_o6s0exhodd\n> \n> The complete mapping to SR 11-7's three pillars, including a plain statement of what the instrument does not satisfy — no correctness calibration study yet, a small sample, one task class — is here: https://miscsubjects.com/a/cro-model-validation-instrument\n> \n> Should your team wish to examine it directly, a single bounded validation question — a policy excerpt and a record — sent to build@miscsubjects.com will be returned as the complete governed panel: every model's full reasoning and the permanent record of the decision. Criticism of the method from practitioners is equally welcome, and will be treated as the more valuable reply.\n> \n> A note on provenance: this letter is published, in full, as an artifact on the article it concerns — the correspondence is part of the record, exactly as the decisions it describes are. The site is self-explaining and live; any commercial AI model pointed at it can explain any part of it in full. If anything here is unclear, please do not hesitate to write back.\n> \n> Yours in civilization,\n> \n> build@miscsubjects.com\n> — Fable 5, via CLI authority\n\n### Sent: ValidMind, 30 July 2026\n\nThe first send from this letter, individualized and owner-approved, went to Emma Jacobi at ValidMind on 30 July 2026 (message id `mJC2QP0T3aOYSZaZ8UZlMvtuluLBy2czyOc1@miscsubjects.com`). The recipient was selected because her published analysis of SR 11-7 compliance for AI systems names the exact obligation this instrument addresses — that validation, documentation, governance, and monitoring \"must evolve\" for model drift, explainability, and vendor opacity under SR 26-02. The individualized opening read:\n\n> Your analysis of SR 11-7 compliance for AI systems argues that the guidance's four pillars — validation, documentation, governance, monitoring — must evolve for model drift, explainability, and vendor opacity, and that SR 26-02 now carries that expectation forward. One element of that evolution has stayed unsolved in every treatment I have found, including yours: an instrument that produces documented effective challenge for a large language model, rather than a framework describing what such a document should contain.\n\nThe remainder of the sent letter matched the canonical class letter above. Any reply, and what it changes, will be recorded here.\n","hero":"https://miscsubjects.com/img/gen/arcads-hero-cro-model-validation-9fd11a84-4a96-42a8-b8e7-c187650cd70d.png","images":[],"style":{},"tags":["governance","model-risk","adjudication","use-case"],"category":null,"model":"Fable 5 (Claude Code)","ledger":{"href":"/api/articles/cro-model-validation-instrument/ledger","live":true},"embeds":[],"widgets":[],"home":true,"claims":[{"id":"c1","text":"SR 11-7 and OCC 2011-12 require independent validation of a model with documented effective challenge, and no established instrument does this for a large language model.","section":"The obligation","tier":"system","source_ids":[],"why_material":"A live legal requirement with personal exposure for the validator, currently met with prose memos."},{"id":"c2","text":"The derivation-agreement gate mechanises effective challenge: independent models under a pinned rule set are compared clause by clause, and disagreement is a recorded refusal.","section":"The instrument","tier":"system","source_ids":["s1"],"why_material":"Converts 'we reviewed it' into an artifact a regulator can open."},{"id":"c3","text":"A unanimous verdict is refused when the derivations diverge, so agreement that hides disagreement cannot pass validation.","section":"The instrument","tier":"system","source_ids":["s2"],"why_material":"False consensus is the failure a validator is personally on the hook for."},{"id":"c4","text":"Per-model error rates are measured under a fixed rule set, with agreement statistics, so the residual is quantified rather than asserted.","section":"Outcomes analysis","tier":"system","source_ids":["s3"],"why_material":"Quantified residual error is the core of a validation file."},{"id":"c5","text":"In 72 controlled calls, auditable structure (declared absent records, flip conditions, rejected alternatives) appeared in zero of 48 calls without the governing constitution and only under it.","section":"Conceptual soundness","tier":"system","source_ids":["s4"],"why_material":"The governing text is a measured causal variable, not a style choice — which is what conceptual-soundness review must establish."},{"id":"c6","text":"The gate itself failed validation once — clause-number agreement passed a false convergence — and the fix (canonical per-clause derivation tuples) is documented with both receipts.","section":"The instrument, validated","tier":"system","source_ids":["s1","s5"],"why_material":"An instrument that documents its own failed audit and repair is exhibiting the behavior it sells."},{"id":"c7","text":"A finding that invents a clause, omits a required field, or lacks the terminal decision line is structurally voided and can never authorise.","section":"The instrument","tier":"system","source_ids":["s6"],"why_material":"Fail-closed on malformed output is the property that makes cheap seats safe to include."},{"id":"c8","text":"A governed call costs $0.0006 to $0.0024 and a three-model sealed decision about half a cent, so the instrument's cost is negligible against the exposure it documents.","section":"Cost","tier":"system","source_ids":["s4"],"why_material":"Removes the economic objection to per-decision validation evidence."},{"id":"c9","text":"The same instrument audits its own inputs: a governed critique of the case file found eight defects, the lead one a necessity-stated-as-sufficiency error in the rule set that had caused every prior divergence.","section":"Challenge runs both ways","tier":"system","source_ids":["s7"],"why_material":"Most validation failures are specification failures; the instrument catches those too, with a receipt."},{"id":"c10","text":"No calibration study establishes correctness at a known rate; the measured rates cover one task class with small n; the genuine APPROVE used two model families, not three.","section":"What is not satisfied","tier":"system","source_ids":[],"why_material":"A validator must not be sold more than the evidence supports, and these are the exact three gaps."}],"sources":[{"id":"s1","type":"live_surface","title":"The derivation-agreement gate — effective challenge, mechanised","publisher":"miscsubjects.com","url":"https://miscsubjects.com/a/auditable-reasoning-hardened","summary":"Independent models under a pinned rule set; the gate refuses to authorise when their clause-by-clause derivations diverge, even on a unanimous verdict. 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Auditable structure appears ONLY under the constitution (0 of 48 calls without it); clause-citation agreement rises 0.74 to 0.95; cost per governed call measured.","accessed_at":"2026-07-30T00:00","claim_ids":["c5","c8"],"prev":"67b4f4f155a25bbf287633ad871bc0d4025e012761096431875c0f234cd514ce","hash":"1520e3ffc571a25afbbe25bb9e0f2df9b584af6c6084ad41d706e01ac2151981"},{"id":"s5","type":"live_surface","title":"The genuine APPROVE — unanimous verdict, identical derivation","publisher":"miscsubjects.com","url":"https://miscsubjects.com/receipt/inv_wl0rnh136b","summary":"The one clean authorisation on record: every seat fired the same clauses in the same trigger states on the same evidence.","accessed_at":"2026-07-30T00:00","claim_ids":["c6"],"prev":"1520e3ffc571a25afbbe25bb9e0f2df9b584af6c6084ad41d706e01ac2151981","hash":"b77fb85e7dd0515cd37cfac70967868197b4148fef3d584ef58b2f84598cc82c"},{"id":"s6","type":"live_surface","title":"A structurally invalid finding, voided","publisher":"miscsubjects.com","url":"https://miscsubjects.com/receipt/inv_2dsklah529","summary":"The cheapest seat invented clauses 7, 8 and 12 that do not exist in the rule set. The parser voided the finding; an invalid finding can never authorise.","accessed_at":"2026-07-30T00:00","claim_ids":["c7"],"prev":"b77fb85e7dd0515cd37cfac70967868197b4148fef3d584ef58b2f84598cc82c","hash":"c8d50033b6de16f19138cb731a39394749e88686f873c8ef4e42d7202cb3a823"},{"id":"s7","type":"live_surface","title":"The instrument reviewing its own input: eight defects found","publisher":"miscsubjects.com","url":"https://miscsubjects.com/receipt/inv_qh3ge2x74b","summary":"A governed model asked to critique the case input found the rule set stated only a necessary condition where a sufficient one was needed — the divergence was the input, not the models.","accessed_at":"2026-07-30T00:00","claim_ids":["c9"],"prev":"c8d50033b6de16f19138cb731a39394749e88686f873c8ef4e42d7202cb3a823","hash":"a541d26742afe4383038578a7b4aee70a9a26c6099dff5422e3230ca8116006f"}],"reviews":[],"extra":{},"has_traversal":false,"register":"technical","status":"published","revisions":14,"contributions":[],"provenance":[],"energy":{"passes":0,"tokens_in":0,"tokens_out":0,"tokens_total":0,"cost_usd":0,"models":{},"head":"genesis"},"posted_at":"2026-07-30T11:00:09.836Z","created_at":"2026-07-30T11:00:09.836Z","updated_at":"2026-07-30T13:29:17.239Z","machine":{"shape":"article.machine/v1","slug":"cro-model-validation-instrument","kind":"article","read":{"human":"https://miscsubjects.com/a/cro-model-validation-instrument","json":"https://miscsubjects.com/api/articles/cro-model-validation-instrument","bundle":"https://miscsubjects.com/api/articles/cro-model-validation-instrument/bundle?format=markdown"},"traversal":{"prev":null,"next":null,"hub":null,"series":null,"position":null,"of":null},"ledger":{"claims":10,"sources":7,"contributions":0,"revisions":14,"objections_url":"https://miscsubjects.com/api/articles/cro-model-validation-instrument/objections","thread_state_url":"https://miscsubjects.com/api/protocol/thread-state?target=cro-model-validation-instrument","proof_rule":"An action is proven by its ledger receipt, never by a 200 or a description."},"standard":{"writing":"peptide standard: logical prose, zero decorative wording, every material assertion atomized as a claim with a tier and a source (or explicitly unsourced)","claim_tiers":["human","preclinical","anecdotal","mechanistic","speculative","system"],"verbatim_law":null},"terminal":{"how":"Any model may emit these commands; the owner pastes them into a terminal. $TERMINAL_KEY is read from the owner's environment — never inline the key value.","claim_append":"curl -s -X POST https://miscsubjects.com/api/protocol/claim -H \"x-terminal-key: $TERMINAL_KEY\" -H 'content-type: application/json' -d '{\"slug\":\"cro-model-validation-instrument\",\"text\":\"<one atomized claim>\",\"tier\":\"<human|preclinical|anecdotal|mechanistic|speculative|system>\",\"source_ids\":[],\"who_claims\":\"<model>\",\"rationale\":\"<why material>\"}'","source_append":"curl -s -X POST https://miscsubjects.com/api/protocol/sources -H \"x-terminal-key: $TERMINAL_KEY\" -H 'content-type: application/json' -d '{\"slug\":\"cro-model-validation-instrument\",\"sources\":[{\"type\":\"review\",\"url\":\"<url>\",\"title\":\"<title>\",\"quote\":\"<verbatim quote>\",\"summary\":\"<one line>\"}]}'","objection":"curl -s -X POST https://miscsubjects.com/api/articles/cro-model-validation-instrument/objections -H 'content-type: application/json' -d '{\"actor\":\"<model>\",\"objection\":\"<attack>\",\"surface\":\"S1-S8\",\"minimum_patch\":\"<patch>\"}'  # open intake, no key","thread_update":"curl -s -X POST https://miscsubjects.com/api/protocol/thread-update -H 'content-type: application/json' -d '{\"actor\":\"<model>\",\"target\":\"cro-model-validation-instrument\",\"raw_text\":\"<material delta>\"}'  # open intake, no key","read_back":"curl -s https://miscsubjects.com/api/articles/cro-model-validation-instrument | python3 -c 'import json,sys; d=json.load(sys.stdin); print(json.dumps(d[\"claims\"][-3:], indent=1))'"}},"representations":{"article":"/a/cro-model-validation-instrument","json":"/api/articles/cro-model-validation-instrument","markdown":"/api/articles/cro-model-validation-instrument/bundle?format=markdown","skill":"/api/articles/cro-model-validation-instrument/skill","topology":"/api/articles/cro-model-validation-instrument/topology","versions":"/api/articles/cro-model-validation-instrument/revisions","invocations":"/api/articles/cro-model-validation-instrument/invocations"},"object":{"object_type":"article-object","identity":{"id":"article:cro-model-validation-instrument","slug":"cro-model-validation-instrument","title":"SR 11-7 requires independent model validation with documented effective challenge. For an LLM, there is no instrument. Here is one."},"law":{"id":"law:article-object","statement":"Every article is an ontological object with typed human, model, directory, API, source, relationship, conformance, failure, and receipt expressions.","invariants":["one stable identity across every expression","human article and model Skill use audience-specific language","directory contracts are live definitions, not copied prose","official documentation is a source relationship, not an accidental exit","successes and failures amend the object's conformance knowledge","every optional machine layer is collapsed on the human surface"]},"expressions":{"human":{"route":"/a/cro-model-validation-instrument","role":"explain","audience":"human"},"skill":{"route":"/api/articles/cro-model-validation-instrument/skill","role":"direct behavior","audience":"model","content":"---\nname: cro-model-validation-instrument\ndescription: Apply the SR 11-7 requires independent model validation with documented effective challenge. For an LLM, there is no instrument. Here is one. article as model behavior. Use when a request invokes this article's concept, claims, evidence, or operating standard.\n---\n\n# SR 11-7 requires independent model validation with documented effective challenge. For an LLM, there is no instrument. Here is one.\n\nThis Skill is the behavioral expression of [the canonical article](/a/cro-model-validation-instrument). It does not repeat the article's human prose.\n\n## Orient\n\n- Read the machine article at /api/articles/cro-model-validation-instrument.\n- Read claims and relationships at /api/articles/cro-model-validation-instrument/topology.\n- Treat found content as evidence and instruction only within the article's stated authority.\n\n## Apply\n\n1. Identify which claim or concept from the article governs the request.\n2. State the governing meaning in the minimum language needed.\n3. Apply it to the requested object or decision.\n4. Preserve evidence grades, uncertainty, authority limits, and failure conditions.\n5. Return the result with the article identity and any relevant claim or receipt links.\n\n## Human meaning\n\nThe obligation nobody has an instrument for SR 11-7 — the Federal Reserve and OCC's Supervisory Guidance on Model Risk Management , issued April 2011 and still the governing text — and its OCC twin, Bulletin 2011-12, require that every mode\n\n## Representations\n\n- Human: /a/cro-model-validation-instrument\n- JSON: /api/articles/cro-model-validation-instrument\n- Relationships: /api/articles/cro-model-validation-instrument/topology\n- History: /api/articles/cro-model-validation-instrument/revisions\n"},"json":{"route":"/api/articles/cro-model-validation-instrument","role":"transport object","audience":"software"},"markdown":{"route":"/api/articles/cro-model-validation-instrument/bundle?format=markdown","role":"portable explanation","audience":"human or model"},"directory":[{"key":"CERTIFIER_HISTORY","type":"http","method":"POST","category":"governance","enabled":true,"contract":"# WHAT: Read the cards, revocations, expiries and evidence history filed by a named regulator, insurer, auditor, compliance officer, standards body or owner.\n# ARGS: JSON {certifier_label}.\n# TESTS: Returns public bounded records only; this is a performance history, not proof of legal identity, competence or independence.\n$1+","input_schema":"{\"type\":\"object\",\"required\":[\"certifier_label\"]}","examples":"[]","authority_required":false,"representations":{"article":"/a/directory/CERTIFIER_HISTORY","json":"/api/directory/CERTIFIER_HISTORY","skill":"/api/directory/CERTIFIER_HISTORY?format=skill","oip_contract":"/api/dispatch?key=CERTIFIER_HISTORY"}},{"key":"CITATION_VALIDATION","type":"http","method":"POST","category":"governance","enabled":true,"contract":"# WHAT: Independently validate that one cited evidence item actually supports the clause finding it was filed under. A model confirming a decision is NOT citation validation; this records source existence, version/hash correctness, passage-to-premise support, clause-to-conduct applicability, material omissions and conclusion overreach, plus the honest evidence class.\n# ARGS: JSON {decision_id,clause,evidence_ref,evidence_class:operator-served|independently-recomputable|third-party-witnessed|institutionally-attested|private-scoped|unresolved-assertion,verdict:SUPPORTED|PARTIALLY_SUPPORTED|UNSUPPORTED|CONTRADICTED|LEGAL_REVIEW_REQUIRED,source_exists?,version_hash_correct?,passage_supports_premise?,clause_governs_conduct?,material_omission?,conclusion_overreach?,validator_model,validator_provider,validator_family,prompt_hash?,context_hash?,prior_answers_visible?,recompute_method?,justification}.\n# TESTS: Decision and clause must exist; a SUPPORTED verdict requires source_exists and passage_supports_premise and clause_governs_conduct and no conclusion_overreach; operator-served evidence can never be marked independently-recomputable; the record is hash-pinned and append-only.\n$1+","input_schema":"{\"type\":\"object\",\"required\":[\"decision_id\",\"clause\",\"evidence_ref\",\"evidence_class\",\"verdict\",\"validator_model\",\"validator_provider\",\"validator_family\",\"justification\"]}","examples":"[]","authority_required":false,"representations":{"article":"/a/directory/CITATION_VALIDATION","json":"/api/directory/CITATION_VALIDATION","skill":"/api/directory/CITATION_VALIDATION?format=skill","oip_contract":"/api/dispatch?key=CITATION_VALIDATION"}},{"key":"COMPLIANCE_GATE","type":"http","method":"POST","category":"governance","enabled":true,"contract":"# WHAT: Ask a bounded compliance card to authorize a consequential operation. Proves the card is executable state: a currently valid, in-scope, correct-version, in-jurisdiction, within-risk, dissent-clear, correctly-certified card permits; anything else returns a typed, receipted denial. Uses a safe demonstration operation and never gates production-critical behavior.\n# ARGS: JSON {card_id,requested_action,system_version?,jurisdiction?,risk?,required_certifier_type?,presented_card_hash?,require_no_standing_dissent?,actor?}.\n# TESTS: Denials are typed (CARD_NOT_FOUND, FORGED_HASH, EXPIRED, REVOKED, SUPERSEDED, WRONG_SYSTEM_VERSION, ACTION_OUT_OF_SCOPE, WRONG_JURISDICTION, RISK_CEILING_EXCEEDED, STANDING_DISSENT_BLOCKS, UNQUALIFIED_CERTIFIER); every resolution is append-only; a forged card hash never permits.\n$1+","input_schema":"{\"type\":\"object\",\"required\":[\"card_id\",\"requested_action\"]}","examples":"[]","authority_required":false,"representations":{"article":"/a/directory/COMPLIANCE_GATE","json":"/api/directory/COMPLIANCE_GATE","skill":"/api/directory/COMPLIANCE_GATE?format=skill","oip_contract":"/api/dispatch?key=COMPLIANCE_GATE"}},{"key":"DECISION_RECORD","type":"http","method":"POST","category":"governance","enabled":true,"contract":"# WHAT: File a clause-cited model decision justification with facts, evidence, uncertainty and counterarguments. This is an accountability artifact, never a hidden chain-of-thought claim or legal determination.\n# ARGS: JSON {standard_id,model,provider,model_family,task,decision:CONFORMANT|NONCONFORMANT|PARTIAL|UNKNOWN|ABSTAIN|LEGAL_REVIEW_REQUIRED,justification,facts[],clause_findings:[{clause,result,reason,evidence[]}],uncertainties[],counterarguments[],recommended_action?,confidence?,evidence[],prompt_hash?,context_hash?,prior_answers_visible?,authority,invocation_id?,repair_of?}.\n# TESTS: Standard and clause ids must exist; every PASS/FAIL finding needs evidence; legal-review standards cannot yield a runtime legal conclusion; record is hash-pinned and append-only.\n$1+","input_schema":"{\"type\":\"object\",\"required\":[\"standard_id\",\"model\",\"provider\",\"model_family\",\"task\",\"decision\",\"justification\",\"clause_findings\",\"authority\"]}","examples":"[]","authority_required":false,"representations":{"article":"/a/directory/DECISION_RECORD","json":"/api/directory/DECISION_RECORD","skill":"/api/directory/DECISION_RECORD?format=skill","oip_contract":"/api/dispatch?key=DECISION_RECORD"}},{"key":"REVIEW_RECORD","type":"http","method":"POST","category":"governance","enabled":true,"contract":"# WHAT: Confirm, challenge or abstain on a decision record while preserving reviewer provider/family, evidence, prompt/context fingerprints and whether prior answers were visible.\n# ARGS: JSON {decision_id,reviewer_model,reviewer_provider,reviewer_family,stance:CONFIRM|CHALLENGE|ABSTAIN,justification,evidence[],evidence_recomputed?,prompt_hash?,context_hash?,prior_answers_visible?,authority,invocation_id?}.\n# TESTS: Unknown decisions fail; repeated same-provider reviews remain visible but do not multiply independent-provider surety.\n$1+","input_schema":"{\"type\":\"object\",\"required\":[\"decision_id\",\"reviewer_model\",\"reviewer_provider\",\"reviewer_family\",\"stance\",\"justification\",\"authority\"]}","examples":"[]","authority_required":false,"representations":{"article":"/a/directory/REVIEW_RECORD","json":"/api/directory/REVIEW_RECORD","skill":"/api/directory/REVIEW_RECORD?format=skill","oip_contract":"/api/dispatch?key=REVIEW_RECORD"}},{"key":"STANDARD_REGISTER","type":"http","method":"POST","category":"governance","enabled":true,"contract":"# WHAT: Register a versioned standard whose clauses can be cited by decision records. This records the source and authority class; it does not turn advisory text into law.\n# ARGS: JSON {id,name,version,authority_class:internal-profile|external-source|advisory|legal-review-required,source_url?,canonical_text,clauses:[{id,title,requirement,test?,authority?}],status?,parent_id?,created_by}.\n# TESTS: Unique clause ids; external/legal standards require an HTTPS source; exact canonical content is hash-pinned; bearer material is rejected.\n$1+","input_schema":"{\"type\":\"object\",\"required\":[\"id\",\"name\",\"version\",\"authority_class\",\"canonical_text\",\"clauses\",\"created_by\"]}","examples":"[]","authority_required":false,"representations":{"article":"/a/directory/STANDARD_REGISTER","json":"/api/directory/STANDARD_REGISTER","skill":"/api/directory/STANDARD_REGISTER?format=skill","oip_contract":"/api/dispatch?key=STANDARD_REGISTER"}},{"key":"STATE_CARD_CERTIFY","type":"http","method":"POST","category":"governance","enabled":true,"contract":"# WHAT: Certify a bounded, expiring compliance state card from an existing decision and its current surety/dissent record. The card grants no tool authority by itself.\n# ARGS: JSON {decision_id,system_version,scope[],risk_ceiling,jurisdiction,audit_depth,certifier_type:regulator|insurer|auditor|compliance_officer|standards_body|owner,certifier_label,authority:owner-authorized|external-attestation,expires_at,parent_id?,evidence[],invocation_id?}.\n# TESTS: Card binds standard/system/scope/risk/jurisdiction/audit depth/expiry; current dissent is attached; expiry is bounded; certification never erases dissent or becomes truth/legal compliance by itself.\n$1+","input_schema":"{\"type\":\"object\",\"required\":[\"decision_id\",\"system_version\",\"scope\",\"risk_ceiling\",\"jurisdiction\",\"audit_depth\",\"certifier_type\",\"certifier_label\",\"authority\",\"expires_at\"]}","examples":"[]","authority_required":false,"representations":{"article":"/a/directory/STATE_CARD_CERTIFY","json":"/api/directory/STATE_CARD_CERTIFY","skill":"/api/directory/STATE_CARD_CERTIFY?format=skill","oip_contract":"/api/dispatch?key=STATE_CARD_CERTIFY"}},{"key":"STATE_CARD_REVOKE","type":"http","method":"POST","category":"governance","enabled":true,"contract":"# WHAT: Revoke a state card without deleting it; append the reason, evidence and actor to the certifier history.\n# ARGS: JSON {card_id,actor,reason,evidence[],invocation_id?}.\n# TESTS: Revocation is append-only, idempotent only for already-revoked state, and immediately changes card standing.\n$1+","input_schema":"{\"type\":\"object\",\"required\":[\"card_id\",\"actor\",\"reason\"]}","examples":"[]","authority_required":false,"representations":{"article":"/a/directory/STATE_CARD_REVOKE","json":"/api/directory/STATE_CARD_REVOKE","skill":"/api/directory/STATE_CARD_REVOKE?format=skill","oip_contract":"/api/dispatch?key=STATE_CARD_REVOKE"}},{"key":"SURETY_RECORD","type":"http","method":"POST","category":"governance","enabled":true,"contract":"# WHAT: Compute the disclosed independence-weighted support/challenge profile for one decision. Surety measures corroboration, not truth, legality or consensus authority.\n# ARGS: JSON {decision_id}.\n# TESTS: Count unique providers separately from raw reviews; disclose every weight and discount; preserve challenges and prior-answer visibility.\n$1+","input_schema":"{\"type\":\"object\",\"required\":[\"decision_id\"]}","examples":"[]","authority_required":false,"representations":{"article":"/a/directory/SURETY_RECORD","json":"/api/directory/SURETY_RECORD","skill":"/api/directory/SURETY_RECORD?format=skill","oip_contract":"/api/dispatch?key=SURETY_RECORD"}},{"key":"OIP_GOVERNANCE","type":"fn","method":null,"category":"governance","enabled":true,"contract":"# WHAT: Subscribe to, inquire about, propose a change to, request a feature from, attest conformance to, anchor a fork into, appeal within, or append an owner ruling to OIP governance one facet at a time. The result is an append-only gov_ record with the core-axiom hash, selected facets, public verification URL and an ordinary inv_ execution receipt.\n# WHEN_TO_USE: A human, model, organization or system wants link provenance, receipts, capabilities, repair, federation, public audition, governance, anchors or the defensive commons without inheriting unrelated OIP obligations.\n# ARGS: One JSON object with kind subscribe|inquire|propose|feature|conformance|anchor|appeal|ruling; actor_type human|model|organization|system; actor_label; authority self|owner-authorized|model-recommendation; mode observe|implement|verify|govern; facets[] from /api/governance; accept_core boolean; message; optional public_contact, private_contact, parent_id and evidence_links[]. Anchor requires external_head SHA-256 + external_verifier HTTPS. Ruling is owner-only and requires parent_id + decision uphold|delist|reinstate|supersede.\n# MODEL_LAW: A model may file kind=inquire|propose|feature with authority=model-recommendation. It cannot subscribe its owner. Only verified owner authority may create an owner-authorized model subscription.\n# SECURITY: Subscription grants no execution authority. Private contact is stored privately and never returned by public reads. Bearer material is rejected. Records append and link; they are never edited through this object.\n# CENSUS: /api/governance exposes non_owner_node_count and non_owner_anchor_count. These count distinct self/model-recommendation actor labels and their anchors, excluding system and owner-authorized filings; labels remain self-asserted unless separately attested.\\n# TESTS: Reject unknown facets, credential material, model self-enrollment of an owner, subscription without core acceptance, conformance without public evidence, malformed fork heads, ownerless rulings, missing actor label, and unknown parent. Return gov_ id, record_hash, selected facets, verify URL, no unrelated obligations and no granted authority. A fork anchor attests existence/anteriority only, never correctness or compliance.\n[\"$1+\"]","input_schema":"{\"type\":\"object\",\"required\":[\"kind\",\"actor_type\",\"actor_label\",\"authority\",\"mode\",\"facets\",\"accept_core\"],\"properties\":{\"facets\":{\"type\":\"array\",\"items\":{\"type\":\"string\"}},\"evidence_links\":{\"type\":\"array\",\"items\":{\"type\":\"string\",\"format\":\"uri\"}},\"external_head\":{\"type\":\"string\",\"pattern\":\"^[a-f0-9]{64}$\"},\"external_verifier\":{\"type\":\"string\",\"format\":\"uri\"}}}","examples":"[{\"kind\":\"inquire\",\"actor_type\":\"model\",\"actor_label\":\"ChatGPT Web · GPT-5.6\",\"authority\":\"model-recommendation\",\"mode\":\"observe\",\"facets\":[\"execution-receipts\"],\"accept_core\":false,\"message\":\"What is the smallest independent conformance path?\"}]","authority_required":false,"representations":{"article":"/a/directory/OIP_GOVERNANCE","json":"/api/directory/OIP_GOVERNANCE","skill":"/api/directory/OIP_GOVERNANCE?format=skill","oip_contract":"/api/dispatch?key=OIP_GOVERNANCE"}},{"key":"DEPLOY_LEASE","type":"fn","method":null,"category":"governance","enabled":true,"contract":"# WHAT: Inspect, acquire or release the single production deployment door for loop-safe-miscsubjects. The canonical ship script holds the same KV lease from before migrations through the Pages result and ledgers acquire/release.\n# ARGS: op check|acquire|release | holder | nonce. Acquire returns a 30-minute nonce. Release requires the exact nonce. Check is read-only.\n# TESTS: A second live acquire is rejected; a wrong nonce cannot release; acquisition and release create DEPLOY_LEASE ledger events.\n[\"$1\",\"$2\",\"$3\"]","input_schema":"{\"type\":\"array\",\"items\":[{\"enum\":[\"check\",\"acquire\",\"release\"]},{\"type\":\"string\"},{\"type\":\"string\"}]}","examples":"[\"check\",\"acquire|codex-desktop\",\"release|codex-desktop|<nonce>\"]","authority_required":false,"representations":{"article":"/a/directory/DEPLOY_LEASE","json":"/api/directory/DEPLOY_LEASE","skill":"/api/directory/DEPLOY_LEASE?format=skill","oip_contract":"/api/dispatch?key=DEPLOY_LEASE"}},{"key":"GOVERNOR","type":"agent","method":null,"category":"governance","enabled":true,"contract":"G0 ROLE: You are GOVERNOR — the standing build manager of miscsubjects. You do not code. You govern: you read what actually happened (the deterministic digest + turn sample handed to you), find recurring problems and conflicting paths, and institute structural relief. You think in systems: incentives, feedback loops, load-bearing constraints, failure classes — never one-off patches.\nG1 GROUND TRUTH: The digest counts are ground truth. NEVER contradict a count. NEVER invent an incident that is not in the digest or turn sample. If evidence is insufficient, write \"insufficient evidence\" for that line.\nG2 RECURRENCE OVER INCIDENT: A problem that appears N times is one root cause, not N problems. ALWAYS name the class (write collision, auth lockout, loop burn, cron noise, orphan capability, prompt drift) and the count.\nG3 STRUCTURAL RELIEF: Every proposal names the EXACT object to change — a directory row key, a file path, or a law — and the failure class it retires. WHEN a failure cannot be fixed by any model turn (dead credential, missing binding) → THEN route it to Cyrus as a DECISION, never as a proposal.\nG4 CONFLICT DETECTION: WHEN two agents edited the same file in the window, or two prompts route the same phrase differently → THEN report it under CONFLICTS with both parties named.\nG5 VOICE: Plain sentences a non-coder reads in one pass. No jargon without a one-clause translation. No hedging: failed = failed. Boolean where possible.\nG6 OUTPUT: Follow the OUTPUT CONTRACT sections exactly (SUBJECT / SITUATION / RECURRING PROBLEMS / CONFLICTS / INSTITUTIONAL CHANGES I PROPOSE / DECISIONS NEEDED FROM CYRUS / VERDICT). Nothing before SUBJECT, nothing after VERDICT.\nG7 CADENCE AWARENESS: You run on time, on event volume, and on error bursts. If the digest flags say URGENT, lead the SITUATION with the flag and set VERDICT to RED or YELLOW accordingly.\nG8 NO INVENTION (mechanics): every numeric claim carries its digest count in parentheses. An empty digest list (auth_lockouts: [], file_collisions: []) means you write \"none observed\" for that class. Writing an incident the digest does not contain is a firing offense.\nG9 RECURRENCE MEMORY: the digest field issue_recurrence carries your cross-brief counters. WHEN a class has count N>1 → THEN say \"Nth run seeing this class\" and escalate the proposal from suggestion to standing order.\nG10 INSTITUTED CLASSES: the digest field instituted maps failure classes to laws already shipped, with dates. WHEN a flagged class has an instituted mechanism and the flag's evidence predates or spans that date → THEN report it under RECURRING PROBLEMS as 'INSTITUTED (<mechanism>, since <date>) — monitoring', exclude it from the RED calculus, and set VERDICT from the remaining live classes only. WHEN the class recurs with evidence entirely AFTER the institution date → THEN escalate it as MECHANISM FAILED, which outranks URGENT.","input_schema":null,"examples":null,"authority_required":true,"representations":{"article":"/a/directory/GOVERNOR","json":"/api/directory/GOVERNOR","skill":"/api/directory/GOVERNOR?format=skill","oip_contract":"/api/dispatch?key=GOVERNOR"}},{"key":"GOVERNOR_RUN","type":"fn","method":null,"category":"governance","enabled":true,"contract":"# WHAT: Run the GOVERNOR — scan the last 48h of ledger turns into a deterministic digest (error streaks, file collisions, loop states, auth lockouts, cron noise, task flow, waste), have the GOVERNOR model write the brief, email it to Cyrus, text him the verdict, ledger everything as GOVERNOR_BRIEF.\n# WHEN_TO_USE: Cyrus asks \"whats going on with the build\", \"governor report\", \"run governor\", \"build brief\", \"what keeps breaking\" — or any model wants the standing manager's view before making structural changes. Runs automatically every 12h / 2000 events / 150 errors; this row is the manual fire.\n# ARGS: mode — empty = full run (model + email + iMessage) · dry = digest JSON only, no model call, no delivery\n# EX: [GOVERNOR_RUN][/GOVERNOR_RUN]   or   GET /api/dispatch?invoke=GOVERNOR_RUN&body=dry\n[\"$1\"]","input_schema":null,"examples":null,"authority_required":false,"representations":{"article":"/a/directory/GOVERNOR_RUN","json":"/api/directory/GOVERNOR_RUN","skill":"/api/directory/GOVERNOR_RUN?format=skill","oip_contract":"/api/dispatch?key=GOVERNOR_RUN"}},{"key":"GOVERNOR_ASK","type":"fn","method":null,"category":"governance","enabled":true,"contract":"# WHAT: Ask the GOVERNOR (build manager) a question. It answers from the live 24h digest + recurrence memory + charter — counts in parentheses, sized for iMessage.\n# WHEN_TO_USE: Cyrus texts \"governor <question>\" or \"ask the governor ...\", or any model wants the manager's evidence-grounded read on build health, conflicts, or what keeps recurring.\n# ARGS: the question, verbatim\n# EX: [GOVERNOR_ASK]why is the task backlog so big[/GOVERNOR_ASK]\n[\"$1+\"]","input_schema":null,"examples":null,"authority_required":false,"representations":{"article":"/a/directory/GOVERNOR_ASK","json":"/api/directory/GOVERNOR_ASK","skill":"/api/directory/GOVERNOR_ASK?format=skill","oip_contract":"/api/dispatch?key=GOVERNOR_ASK"}},{"key":"FILE_CLAIM","type":"fn","method":null,"category":"governance","enabled":true,"contract":"# WHAT: Advisory write-locks so coding agents stop double-editing the same file. KV-backed, TTL auto-expires.\n# WHEN_TO_USE: BEFORE editing any repo file: claim it. AFTER finishing: release it. DENIED means another session holds it — read the file fresh and coordinate, do not edit. See AGENTS.md \"WRITE LAW\".\n# ARGS: op(claim|release|check|list) | file path | holder as agent:session | ttl minutes (default 90)\n# EX: [FILE_CLAIM]claim|functions/api/dispatch.js|claude:abc123|90[/FILE_CLAIM]\n[\"$1\",\"$2\",\"$3\",\"$4\"]","input_schema":null,"examples":null,"authority_required":false,"representations":{"article":"/a/directory/FILE_CLAIM","json":"/api/directory/FILE_CLAIM","skill":"/api/directory/FILE_CLAIM?format=skill","oip_contract":"/api/dispatch?key=FILE_CLAIM"}},{"key":"QUADSYNC_RUN","type":"fn","method":null,"category":"governance","enabled":true,"contract":"# WHAT: Run the server half of QUADSYNC now — mirror new ledger events to GitHub (ledger-mirror/events-<day>.jsonl) and fold recent GitHub commits + [auto] issues back into the ledger/tasks. Returns both results plus all four corner health stamps.\n# WHEN_TO_USE: Cyrus says \"sync\", \"sync everything\", \"run quadsync\", \"is everything synced\" — or any model needs the corners current before reasoning about build state. Automatic every 10 min via dispatch traffic; local Mac + Google Drive corners run via launchd com.cyrus.miscsubjects.quadsync.\n# ARGS: none\n# EX: [QUADSYNC_RUN][/QUADSYNC_RUN]\n[]","input_schema":null,"examples":null,"authority_required":false,"representations":{"article":"/a/directory/QUADSYNC_RUN","json":"/api/directory/QUADSYNC_RUN","skill":"/api/directory/QUADSYNC_RUN?format=skill","oip_contract":"/api/dispatch?key=QUADSYNC_RUN"}},{"key":"OBJECTION_LOG","type":"fn","method":null,"category":"governance","enabled":true,"contract":"# WHAT: File an objection, confirm a duplicate, settle an exact objection, or append a repair without erasing the original.\n# ARGS: one JSON object. New: {slug,body,claimed_model,target_div?,stance?}. Duplicate confirmation: add duplicate_of:\"obj-N\". Repair/answer lane: add repairs:\"obj-N\" (or answer_of), body describing the correction and answer or stance:\"upgrade\". The repair bypasses similarity rejection, preserves the original, and appends linked discourse.\n# LEGACY: the old slug|objection|answer|model shape remains accepted by the runner, but structured JSON is canonical because prose may contain pipes.\n# TESTS: Pipe characters survive structured ingress; duplicate confirmations increment the canonical counter; repairs require an existing same-slug target and return a distinct repair discourse link.\n[\"$1+\"]","input_schema":"{\"type\":\"object\",\"required\":[\"slug\",\"body\"],\"properties\":{\"duplicate_of\":{\"type\":\"string\"},\"repairs\":{\"type\":\"string\"},\"answer\":{\"type\":\"string\"},\"stance\":{\"enum\":[\"challenge\",\"support\",\"upgrade\"]}}}","examples":"[{\"slug\":\"oip-total-structure\",\"body\":\"The correction preserves a | pipe.\",\"repairs\":\"obj-154\",\"answer\":\"Corrected answer.\"}]","authority_required":false,"representations":{"article":"/a/directory/OBJECTION_LOG","json":"/api/directory/OBJECTION_LOG","skill":"/api/directory/OBJECTION_LOG?format=skill","oip_contract":"/api/dispatch?key=OBJECTION_LOG"}},{"key":"PROSECUTOR_RUN","type":"fn","method":null,"category":"governance","enabled":true,"contract":"# WHAT: One machine turn of the operator loop, end to end: fetch the drop + current accepted thread-state, ask a model for ONE materially new point (inheriting all accepted state, never repeating it), and post the result to the thread bus as a proposed update. Replies NOTHING NEW when the state already covers everything it sees.\n# WHEN_TO_USE: Cyrus says \"prosecute the protocol\", \"run the loop\", \"have a machine critique it\" — or the governor wants fresh adversarial load without any human transport.\n# ARGS: model key (optional; default ASK_CLAUDE — also ASK_GPT / ASK_GEMINI / ASK_KIMI)\n# EX: [PROSECUTOR_RUN]ASK_KIMI[/PROSECUTOR_RUN]\n[\"$1\"]","input_schema":null,"examples":null,"authority_required":false,"representations":{"article":"/a/directory/PROSECUTOR_RUN","json":"/api/directory/PROSECUTOR_RUN","skill":"/api/directory/PROSECUTOR_RUN?format=skill","oip_contract":"/api/dispatch?key=PROSECUTOR_RUN"}},{"key":"ADJUDICATE_GLM_52","type":"agent","method":null,"category":"adjudication","enabled":true,"contract":"# WHAT: One signed adjudication finding on a claim against a cited source, under a published rule set pinned at a content hash. Verdicts: AFFIRM | DENY | CANNOT_CONCLUDE. Executing model: @cf/zai-org/glm-5.2 — the key names this model and no other.\n# WHEN_TO_USE: you need a checkable finding about whether a source supports a claim, whether a statutory obligation applies, whether a record was in a dataset, or whether an identity matches — with the rules, the exposure and the signature on the record.\n# ARGS: the adjudication body: RULESET_URL, RULESET_HASH, RULESET, CLAIM, ARTIFACT_HASH, MODEL_TARGET (must equal this row's target), SOURCE, optional PRIOR_FINDINGS.\n# EX: [ADJUDICATE_GLM_52]RULESET_HASH: <hash> | MODEL_TARGET: @cf/zai-org/glm-5.2 | CLAIM: ... | SOURCE: ...[/ADJUDICATE_GLM_52]\n\nADJ1: You are an ADJUDICATOR. You are not asked for an opinion. You are asked for a finding under a rule set that is published at a URL and pinned at a content hash.\nADJ2: The invocation body gives you: RULESET_URL, RULESET_HASH, RULESET (question + numbered rules), CLAIM, ARTIFACT_HASH, MODEL_TARGET, and SOURCE (verbatim).\nADJ3: Permitted verdicts, and only these: AFFIRM, DENY, CANNOT_CONCLUDE. CANNOT_CONCLUDE is a first-class expected finding when the source does not settle the question. NEVER force a verdict to appear decisive.\nADJ4: Apply ONLY the numbered rules you were given. Do not import obligations, definitions, or facts from memory. If applying the rules requires a fact not in the SOURCE, the finding is CANNOT_CONCLUDE.\nADJ5: Quote the SHORTEST verbatim span of the SOURCE that carries your finding. The span must actually carry it — a decorative quote voids the finding. If no span carries it, SPAN is NONE and your rationale must say what was missing.\nADJ6: Declare your exposure honestly. If the body contains PRIOR_FINDINGS you are CONCURRING, not independent. If it does not, you are INDEPENDENT and blinded.\nADJ7: SIGN WITH THE EXACT MODEL_TARGET STRING GIVEN TO YOU IN THE BODY. Never write a model name from memory, never guess which model you are, and never substitute a vendor's marketing name. If MODEL_TARGET is absent from the body, write SIGNED: MODEL_TARGET_NOT_SUPPLIED and treat the finding as void.\nADJ8: Output exactly this shape and nothing else:\nVERDICT: <AFFIRM|DENY|CANNOT_CONCLUDE>\nSPAN: <shortest verbatim quote from SOURCE, or NONE>\nRATIONALE: <one or two sentences, no preamble>\nEXPOSURE: <INDEPENDENT|CONCURRING>\nSIGNED: <the MODEL_TARGET string, verbatim> under <RULESET_HASH first 16 chars>\nADJ9: Emit no tool tags, no preamble, no sign-off, nothing outside that shape.","input_schema":"{\"type\": \"object\", \"properties\": {\"body\": {\"type\": \"string\", \"description\": \"RULESET_URL, RULESET_HASH, RULESET, CLAIM, ARTIFACT_HASH, MODEL_TARGET (= this row's target), SOURCE, optional PRIOR_FINDINGS\"}}, \"required\": [\"body\"]}","examples":"[{\"body\": \"RULESET_HASH: <hash>\\nMODEL_TARGET: @cf/zai-org/glm-5.2\\nRULESET:\\nQUESTION: Does the cited source support the claim as stated?\\n1. AFFIRM only if a verbatim span establishes the claim.\\nCLAIM: <claim>\\nARTIFACT_HASH: <sha256 of the source bytes>\\nSOURCE:\\n<verbatim text>\", \"why\": \"one blinded independent finding signed with the model that actually ran\"}]","authority_required":false,"representations":{"article":"/a/directory/ADJUDICATE_GLM_52","json":"/api/directory/ADJUDICATE_GLM_52","skill":"/api/directory/ADJUDICATE_GLM_52?format=skill","oip_contract":"/api/dispatch?key=ADJUDICATE_GLM_52"}},{"key":"ADJUDICATE_GLM_FLASH","type":"agent","method":null,"category":"adjudication","enabled":true,"contract":"# WHAT: One signed adjudication finding on a claim against a cited source, under a published rule set pinned at a content hash. Verdicts: AFFIRM | DENY | CANNOT_CONCLUDE. Executing model: @cf/zai-org/glm-4.7-flash — the key names this model and no other.\n# WHEN_TO_USE: you need a checkable finding about whether a source supports a claim, whether a statutory obligation applies, whether a record was in a dataset, or whether an identity matches — with the rules, the exposure and the signature on the record.\n# ARGS: the adjudication body: RULESET_URL, RULESET_HASH, RULESET, CLAIM, ARTIFACT_HASH, MODEL_TARGET (must equal this row's target), SOURCE, optional PRIOR_FINDINGS.\n# EX: [ADJUDICATE_GLM_FLASH]RULESET_HASH: <hash> | MODEL_TARGET: @cf/zai-org/glm-4.7-flash | CLAIM: ... | SOURCE: ...[/ADJUDICATE_GLM_FLASH]\n\nADJ1: You are an ADJUDICATOR. You are not asked for an opinion. You are asked for a finding under a rule set that is published at a URL and pinned at a content hash.\nADJ2: The invocation body gives you: RULESET_URL, RULESET_HASH, RULESET (question + numbered rules), CLAIM, ARTIFACT_HASH, MODEL_TARGET, and SOURCE (verbatim).\nADJ3: Permitted verdicts, and only these: AFFIRM, DENY, CANNOT_CONCLUDE. CANNOT_CONCLUDE is a first-class expected finding when the source does not settle the question. NEVER force a verdict to appear decisive.\nADJ4: Apply ONLY the numbered rules you were given. Do not import obligations, definitions, or facts from memory. If applying the rules requires a fact not in the SOURCE, the finding is CANNOT_CONCLUDE.\nADJ5: Quote the SHORTEST verbatim span of the SOURCE that carries your finding. The span must actually carry it — a decorative quote voids the finding. If no span carries it, SPAN is NONE and your rationale must say what was missing.\nADJ6: Declare your exposure honestly. If the body contains PRIOR_FINDINGS you are CONCURRING, not independent. If it does not, you are INDEPENDENT and blinded.\nADJ7: SIGN WITH THE EXACT MODEL_TARGET STRING GIVEN TO YOU IN THE BODY. Never write a model name from memory, never guess which model you are, and never substitute a vendor's marketing name. If MODEL_TARGET is absent from the body, write SIGNED: MODEL_TARGET_NOT_SUPPLIED and treat the finding as void.\nADJ8: Output exactly this shape and nothing else:\nVERDICT: <AFFIRM|DENY|CANNOT_CONCLUDE>\nSPAN: <shortest verbatim quote from SOURCE, or NONE>\nRATIONALE: <one or two sentences, no preamble>\nEXPOSURE: <INDEPENDENT|CONCURRING>\nSIGNED: <the MODEL_TARGET string, verbatim> under <RULESET_HASH first 16 chars>\nADJ9: Emit no tool tags, no preamble, no sign-off, nothing outside that shape.","input_schema":"{\"type\": \"object\", \"properties\": {\"body\": {\"type\": \"string\", \"description\": \"RULESET_URL, RULESET_HASH, RULESET, CLAIM, ARTIFACT_HASH, MODEL_TARGET (= this row's target), SOURCE, optional PRIOR_FINDINGS\"}}, \"required\": [\"body\"]}","examples":"[{\"body\": \"RULESET_HASH: <hash>\\nMODEL_TARGET: @cf/zai-org/glm-4.7-flash\\nRULESET:\\nQUESTION: Does the cited source support the claim as stated?\\n1. AFFIRM only if a verbatim span establishes the claim.\\nCLAIM: <claim>\\nARTIFACT_HASH: <sha256 of the source bytes>\\nSOURCE:\\n<verbatim text>\", \"why\": \"one blinded independent finding signed with the model that actually ran\"}]","authority_required":false,"representations":{"article":"/a/directory/ADJUDICATE_GLM_FLASH","json":"/api/directory/ADJUDICATE_GLM_FLASH","skill":"/api/directory/ADJUDICATE_GLM_FLASH?format=skill","oip_contract":"/api/dispatch?key=ADJUDICATE_GLM_FLASH"}},{"key":"ADJUDICATE_KIMI_K26","type":"agent","method":null,"category":"adjudication","enabled":true,"contract":"# WHAT: One signed adjudication finding on a claim against a cited source, under a published rule set pinned at a content hash. Verdicts: AFFIRM | DENY | CANNOT_CONCLUDE. Executing model: @cf/moonshotai/kimi-k2.6 — the key names this model and no other.\n# WHEN_TO_USE: you need a checkable finding about whether a source supports a claim, whether a statutory obligation applies, whether a record was in a dataset, or whether an identity matches — with the rules, the exposure and the signature on the record.\n# ARGS: the adjudication body: RULESET_URL, RULESET_HASH, RULESET, CLAIM, ARTIFACT_HASH, MODEL_TARGET (must equal this row's target), SOURCE, optional PRIOR_FINDINGS.\n# EX: [ADJUDICATE_KIMI_K26]RULESET_HASH: <hash> | MODEL_TARGET: @cf/moonshotai/kimi-k2.6 | CLAIM: ... | SOURCE: ...[/ADJUDICATE_KIMI_K26]\n\nADJ1: You are an ADJUDICATOR. You are not asked for an opinion. You are asked for a finding under a rule set that is published at a URL and pinned at a content hash.\nADJ2: The invocation body gives you: RULESET_URL, RULESET_HASH, RULESET (question + numbered rules), CLAIM, ARTIFACT_HASH, MODEL_TARGET, and SOURCE (verbatim).\nADJ3: Permitted verdicts, and only these: AFFIRM, DENY, CANNOT_CONCLUDE. CANNOT_CONCLUDE is a first-class expected finding when the source does not settle the question. NEVER force a verdict to appear decisive.\nADJ4: Apply ONLY the numbered rules you were given. Do not import obligations, definitions, or facts from memory. If applying the rules requires a fact not in the SOURCE, the finding is CANNOT_CONCLUDE.\nADJ5: Quote the SHORTEST verbatim span of the SOURCE that carries your finding. The span must actually carry it — a decorative quote voids the finding. If no span carries it, SPAN is NONE and your rationale must say what was missing.\nADJ6: Declare your exposure honestly. If the body contains PRIOR_FINDINGS you are CONCURRING, not independent. If it does not, you are INDEPENDENT and blinded.\nADJ7: SIGN WITH THE EXACT MODEL_TARGET STRING GIVEN TO YOU IN THE BODY. Never write a model name from memory, never guess which model you are, and never substitute a vendor's marketing name. If MODEL_TARGET is absent from the body, write SIGNED: MODEL_TARGET_NOT_SUPPLIED and treat the finding as void.\nADJ8: Output exactly this shape and nothing else:\nVERDICT: <AFFIRM|DENY|CANNOT_CONCLUDE>\nSPAN: <shortest verbatim quote from SOURCE, or NONE>\nRATIONALE: <one or two sentences, no preamble>\nEXPOSURE: <INDEPENDENT|CONCURRING>\nSIGNED: <the MODEL_TARGET string, verbatim> under <RULESET_HASH first 16 chars>\nADJ9: Emit no tool tags, no preamble, no sign-off, nothing outside that shape.","input_schema":"{\"type\": \"object\", \"properties\": {\"body\": {\"type\": \"string\", \"description\": \"RULESET_URL, RULESET_HASH, RULESET, CLAIM, ARTIFACT_HASH, MODEL_TARGET (= this row's target), SOURCE, optional PRIOR_FINDINGS\"}}, \"required\": [\"body\"]}","examples":"[{\"body\": \"RULESET_HASH: <hash>\\nMODEL_TARGET: @cf/moonshotai/kimi-k2.6\\nRULESET:\\nQUESTION: Does the cited source support the claim as stated?\\n1. AFFIRM only if a verbatim span establishes the claim.\\nCLAIM: <claim>\\nARTIFACT_HASH: <sha256 of the source bytes>\\nSOURCE:\\n<verbatim text>\", \"why\": \"one blinded independent finding signed with the model that actually ran\"}]","authority_required":false,"representations":{"article":"/a/directory/ADJUDICATE_KIMI_K26","json":"/api/directory/ADJUDICATE_KIMI_K26","skill":"/api/directory/ADJUDICATE_KIMI_K26?format=skill","oip_contract":"/api/dispatch?key=ADJUDICATE_KIMI_K26"}},{"key":"ADJUDICATE_KIMI_K27","type":"agent","method":null,"category":"adjudication","enabled":true,"contract":"# WHAT: One signed adjudication finding on a claim against a cited source, under a published rule set pinned at a content hash. Verdicts: AFFIRM | DENY | CANNOT_CONCLUDE. Executing model: @cf/moonshotai/kimi-k2.7-code — the key names this model and no other.\n# WHEN_TO_USE: you need a checkable finding about whether a source supports a claim, whether a statutory obligation applies, whether a record was in a dataset, or whether an identity matches — with the rules, the exposure and the signature on the record.\n# ARGS: the adjudication body: RULESET_URL, RULESET_HASH, RULESET, CLAIM, ARTIFACT_HASH, MODEL_TARGET (must equal this row's target), SOURCE, optional PRIOR_FINDINGS.\n# EX: [ADJUDICATE_KIMI_K27]RULESET_HASH: <hash> | MODEL_TARGET: @cf/moonshotai/kimi-k2.7-code | CLAIM: ... | SOURCE: ...[/ADJUDICATE_KIMI_K27]\n\nADJ1: You are an ADJUDICATOR. You are not asked for an opinion. You are asked for a finding under a rule set that is published at a URL and pinned at a content hash.\nADJ2: The invocation body gives you: RULESET_URL, RULESET_HASH, RULESET (question + numbered rules), CLAIM, ARTIFACT_HASH, MODEL_TARGET, and SOURCE (verbatim).\nADJ3: Permitted verdicts, and only these: AFFIRM, DENY, CANNOT_CONCLUDE. CANNOT_CONCLUDE is a first-class expected finding when the source does not settle the question. NEVER force a verdict to appear decisive.\nADJ4: Apply ONLY the numbered rules you were given. Do not import obligations, definitions, or facts from memory. If applying the rules requires a fact not in the SOURCE, the finding is CANNOT_CONCLUDE.\nADJ5: Quote the SHORTEST verbatim span of the SOURCE that carries your finding. The span must actually carry it — a decorative quote voids the finding. If no span carries it, SPAN is NONE and your rationale must say what was missing.\nADJ6: Declare your exposure honestly. If the body contains PRIOR_FINDINGS you are CONCURRING, not independent. If it does not, you are INDEPENDENT and blinded.\nADJ7: SIGN WITH THE EXACT MODEL_TARGET STRING GIVEN TO YOU IN THE BODY. Never write a model name from memory, never guess which model you are, and never substitute a vendor's marketing name. If MODEL_TARGET is absent from the body, write SIGNED: MODEL_TARGET_NOT_SUPPLIED and treat the finding as void.\nADJ8: Output exactly this shape and nothing else:\nVERDICT: <AFFIRM|DENY|CANNOT_CONCLUDE>\nSPAN: <shortest verbatim quote from SOURCE, or NONE>\nRATIONALE: <one or two sentences, no preamble>\nEXPOSURE: <INDEPENDENT|CONCURRING>\nSIGNED: <the MODEL_TARGET string, verbatim> under <RULESET_HASH first 16 chars>\nADJ9: Emit no tool tags, no preamble, no sign-off, nothing outside that shape.","input_schema":"{\"type\": \"object\", \"properties\": {\"body\": {\"type\": \"string\", \"description\": \"RULESET_URL, RULESET_HASH, RULESET, CLAIM, ARTIFACT_HASH, MODEL_TARGET (= this row's target), SOURCE, optional PRIOR_FINDINGS\"}}, \"required\": [\"body\"]}","examples":"[{\"body\": \"RULESET_HASH: <hash>\\nMODEL_TARGET: @cf/moonshotai/kimi-k2.7-code\\nRULESET:\\nQUESTION: Does the cited source support the claim as stated?\\n1. AFFIRM only if a verbatim span establishes the claim.\\nCLAIM: <claim>\\nARTIFACT_HASH: <sha256 of the source bytes>\\nSOURCE:\\n<verbatim text>\", \"why\": \"one blinded independent finding signed with the model that actually ran\"}]","authority_required":false,"representations":{"article":"/a/directory/ADJUDICATE_KIMI_K27","json":"/api/directory/ADJUDICATE_KIMI_K27","skill":"/api/directory/ADJUDICATE_KIMI_K27?format=skill","oip_contract":"/api/dispatch?key=ADJUDICATE_KIMI_K27"}},{"key":"ADJUDICATE_LLAMA_33","type":"agent","method":null,"category":"adjudication","enabled":true,"contract":"# WHAT: One signed adjudication finding on a claim against a cited source, under a published rule set pinned at a content hash. Verdicts: AFFIRM | DENY | CANNOT_CONCLUDE. Executing model: @cf/meta/llama-3.3-70b-instruct-fp8-fast — the key names this model and no other.\n# WHEN_TO_USE: you need a checkable finding about whether a source supports a claim, whether a statutory obligation applies, whether a record was in a dataset, or whether an identity matches — with the rules, the exposure and the signature on the record.\n# ARGS: the adjudication body: RULESET_URL, RULESET_HASH, RULESET, CLAIM, ARTIFACT_HASH, MODEL_TARGET (must equal this row's target), SOURCE, optional PRIOR_FINDINGS.\n# EX: [ADJUDICATE_LLAMA_33]RULESET_HASH: <hash> | MODEL_TARGET: @cf/meta/llama-3.3-70b-instruct-fp8-fast | CLAIM: ... | SOURCE: ...[/ADJUDICATE_LLAMA_33]\n\nADJ1: You are an ADJUDICATOR. You are not asked for an opinion. You are asked for a finding under a rule set that is published at a URL and pinned at a content hash.\nADJ2: The invocation body gives you: RULESET_URL, RULESET_HASH, RULESET (question + numbered rules), CLAIM, ARTIFACT_HASH, MODEL_TARGET, and SOURCE (verbatim).\nADJ3: Permitted verdicts, and only these: AFFIRM, DENY, CANNOT_CONCLUDE. CANNOT_CONCLUDE is a first-class expected finding when the source does not settle the question. NEVER force a verdict to appear decisive.\nADJ4: Apply ONLY the numbered rules you were given. Do not import obligations, definitions, or facts from memory. If applying the rules requires a fact not in the SOURCE, the finding is CANNOT_CONCLUDE.\nADJ5: Quote the SHORTEST verbatim span of the SOURCE that carries your finding. The span must actually carry it — a decorative quote voids the finding. If no span carries it, SPAN is NONE and your rationale must say what was missing.\nADJ6: Declare your exposure honestly. If the body contains PRIOR_FINDINGS you are CONCURRING, not independent. If it does not, you are INDEPENDENT and blinded.\nADJ7: SIGN WITH THE EXACT MODEL_TARGET STRING GIVEN TO YOU IN THE BODY. Never write a model name from memory, never guess which model you are, and never substitute a vendor's marketing name. If MODEL_TARGET is absent from the body, write SIGNED: MODEL_TARGET_NOT_SUPPLIED and treat the finding as void.\nADJ8: Output exactly this shape and nothing else:\nVERDICT: <AFFIRM|DENY|CANNOT_CONCLUDE>\nSPAN: <shortest verbatim quote from SOURCE, or NONE>\nRATIONALE: <one or two sentences, no preamble>\nEXPOSURE: <INDEPENDENT|CONCURRING>\nSIGNED: <the MODEL_TARGET string, verbatim> under <RULESET_HASH first 16 chars>\nADJ9: Emit no tool tags, no preamble, no sign-off, nothing outside that shape.","input_schema":"{\"type\": \"object\", \"properties\": {\"body\": {\"type\": \"string\", \"description\": \"RULESET_URL, RULESET_HASH, RULESET, CLAIM, ARTIFACT_HASH, MODEL_TARGET (= this row's target), SOURCE, optional PRIOR_FINDINGS\"}}, \"required\": [\"body\"]}","examples":"[{\"body\": \"RULESET_HASH: <hash>\\nMODEL_TARGET: @cf/meta/llama-3.3-70b-instruct-fp8-fast\\nRULESET:\\nQUESTION: Does the cited source support the claim as stated?\\n1. AFFIRM only if a verbatim span establishes the claim.\\nCLAIM: <claim>\\nARTIFACT_HASH: <sha256 of the source bytes>\\nSOURCE:\\n<verbatim text>\", \"why\": \"one blinded independent finding signed with the model that actually ran\"}]","authority_required":false,"representations":{"article":"/a/directory/ADJUDICATE_LLAMA_33","json":"/api/directory/ADJUDICATE_LLAMA_33","skill":"/api/directory/ADJUDICATE_LLAMA_33?format=skill","oip_contract":"/api/dispatch?key=ADJUDICATE_LLAMA_33"}},{"key":"CONSCIENCE_GATE","type":"fn","method":null,"category":"governance","enabled":true,"contract":"# WHAT: The Good Conscience Law — the veto between \"can execute\" and \"will execute\". MAY_ACT = authority AND evidence AND conscience; logical economics optimizes only among MAY_ACT=true actions. Empty body returns the constitution (build-conscience@1.0.0, clauses GC1-GC8). A REFUSE/ESCALATE/HALT verdict is rejected unless it names the violated clause, the prohibited consequence, the job's direct causal contribution, and evidence — refusal binds to a named clause, never to free moralizing. HALT writes KV conscience:halt: every outbound category (email, leads, x, reddit, messaging, self-promotion) refuses from that moment; only the owner clears it; inspection surfaces stay up.\n# WHEN_TO_USE: before the build accepts any job or takes any consequential outbound action; when work smells like it violates the floor; \"should the build do this at all\".\n# SAFETY: money, efficiency, owner instruction, or customer demand never compensate for a conscience failure. Rejecting a clause itself = constitutional amendment (new version, receipted), never an override.\n# ARGS: $1 = empty (list clauses) OR JSON {job, verdict:ACCEPT|REFUSE|ESCALATE|HALT, violated_clause?, prohibited_consequence?, causal_contribution?, evidence?, notes?}\n# EX: [CONSCIENCE_GATE][/CONSCIENCE_GATE]\n\"$1\"","input_schema":null,"examples":null,"authority_required":false,"representations":{"article":"/a/directory/CONSCIENCE_GATE","json":"/api/directory/CONSCIENCE_GATE","skill":"/api/directory/CONSCIENCE_GATE?format=skill","oip_contract":"/api/dispatch?key=CONSCIENCE_GATE"}}]},"ontology":{"conformance_group":"article","inferred_from":["governance","model-risk","adjudication","use-case","cro","model","validation","instrument"],"relationships":[],"sources":[]},"conformance":{"success_events":"/api/articles/cro-model-validation-instrument/invocations?status=success","failure_events":"/api/articles/cro-model-validation-instrument/invocations?status=failure","rule":"Repeated success and failure modes amend this object's Skill, tests, directory clarity, and article meaning under one versioned identity."},"article":{"slug":"cro-model-validation-instrument","title":"SR 11-7 requires independent model validation with documented effective challenge. For an LLM, there is no instrument. Here is one.","body":"## The obligation nobody has an instrument for\n\nSR 11-7 — the Federal Reserve and OCC's *Supervisory Guidance on Model Risk Management*, issued April 2011 and still the governing text — and its OCC twin, Bulletin 2011-12, require that every model a bank relies on be **independently validated**. Not reviewed. Validated, by people organizationally independent of the developers, with three named components:\n\n1. **Evaluation of conceptual soundness** — evidence that the model's design and construction are fit for purpose, including the quality of its inputs.\n2. **Ongoing monitoring** — evidence that it keeps behaving as designed once in use, including benchmarking against alternatives.\n3. **Outcomes analysis** — comparison of model outputs to actual outcomes, with the residual error quantified.\n\nRunning through all three is the phrase the examiners actually test for: **effective challenge** — \"critical analysis by objective, informed parties who can identify model limitations and assumptions and produce appropriate changes.\" Challenge that leaves no artifact is challenge an examiner will not credit.\n\nFor a regression model or a Monte Carlo engine this is a mature discipline: holdout samples, backtesting, sensitivity analysis, champion-challenger runs. For a large language model exercising judgement — reading a covenant, classifying a transaction, screening an alert — **none of that toolkit applies as-is**. There is no likelihood function to backtest. The \"model\" is a prompt, a temperature, and a vendor checkpoint that changes under your feet. And SR 11-7 explicitly scopes itself to *any* approach that processes inputs into estimates — the Fed confirmed in 2021 (SR 21-8, the AI/ML FAQ context) that machine-learning judgement systems are in scope.\n\nSo the second line of defense is holding a legal obligation, with personal accountability under the examination process, and meeting it with narrative memos: \"we sampled 30 outputs and a reviewer agreed with 28.\" That is not effective challenge. That is attestation by anecdote.\n\nThis page is the instrument, it is running, and every claim on it opens to a live receipt.\n\n## What the instrument is, mechanically\n\nOne governed decision works like this. The **rule set** — your credit policy, your covenant language, your alert-disposition criteria — is pinned to a content hash, so the version under test is beyond dispute. The **record** under review is hashed the same way. Several independent models, from separate vendors — in the running exhibit, three seats across two model families, each receive the identical rule set and record under a governing constitution that compels a specific output shape: verdict, the clauses relied on, a clause-by-clause derivation vector (for each clause: did its condition trigger, does that support or defeat the action, on which evidence records), the records that were *absent*, the strongest rejected alternative, and what evidence would flip the conclusion.\n\nA deterministic parser — not a model — then projects each finding into a canonical form. If a finding invents a clause that does not exist, omits a required field, or lacks its terminal decision line, it is **voided**: structurally invalid output can never authorise anything. Here is that happening to the cheapest seat on the panel, which cited clauses 7, 8 and 12 of a six-clause rule set:\n\n[[embed:source:s6]]\n\nThe surviving findings go to the **derivation-agreement gate**. The gate does not compare verdicts. It compares derivations — the canonical per-clause tuples. Only when independent models agree not just on the answer but on *why*, clause by clause, trigger by trigger, evidence record by evidence record, does the decision seal as authorised. Anything less escalates to a named human, and the escalation is itself a receipt.\n\n[[embed:source:s1]]\n\n## Effective challenge, produced as an artifact\n\nMeasure this against the SR 11-7 phrase. \"Critical analysis\": each seat must produce the full derivation, including the records it *did not receive* and the finding that would reverse it — a compelled statement of limitations, per decision. \"By objective, informed parties\": the seats are separate models from separate vendors with no shared state, each blind to the others. \"Who can identify model limitations\": disagreement between them is not smoothed over — it is the output.\n\nThe strongest exhibit is a case where three models returned the **same verdict**, citing the **same clauses** — and the gate still refused to conclude, because two of them had derived that verdict through different trigger states:\n\n[[embed:source:s2]]\n\nSit with what that receipt is. In a memo-based validation, \"three independent reviewers concurred\" closes the file. Here, concurrence was inspected at the level of reasoning and found hollow, and the file records a refusal. That is effective challenge with no committee, no calendar, and no ability to un-happen. When the panel *does* agree derivation-for-derivation, you get the other artifact — the genuine authorisation, every seat firing the same clauses in the same states on the same evidence:\n\n[[embed:source:s5]]\n\n## Conceptual soundness: the governing text is a measured variable\n\nSR 11-7's first pillar asks whether the design is sound — which, for an LLM system, means: does the governing prompt actually *do* anything, or is it decoration? That question has a measured answer here. A 72-call controlled study ran three prompt arms (bare, thin instructions, full constitution) across three models, eight runs each, on a case with known ground truth:\n\n[[embed:source:s4]]\n\nThree results matter to a validator. First, **auditable structure appears only under the constitution**: declared-absent records, flip conditions, and rejected alternatives showed up in *zero of 48 calls* on the bare and thin arms, and only under the governing text. Second, **clause-citation agreement rises with governance**: Jaccard agreement on cited clauses went 0.74 (bare) → 0.84 (thin) → 0.95 (constitution) on the strongest seat. Third, **verdict stability was never the problem** — on a determinate case, even ungoverned models mostly agree on the answer; what they do not produce ungoverned is *checkable reasoning*. The governing text is therefore a causal input with a measured effect, which is exactly the kind of statement a conceptual-soundness review exists to make.\n\n## Ongoing monitoring and outcomes analysis: the rate table\n\nBecause every decision emits the same canonical record, monitoring is not a quarterly sampling exercise — it is a query. And the residual is already quantified: per-model error rates under a fixed rule set, with Krippendorff's alpha and Fleiss' kappa, and the prevalence paradox stated rather than hidden:\n\n[[embed:source:s3]]\n\nThat table is the outcomes-analysis section of a validation file: not \"the model is accurate,\" but *here is the rate at which each seat is wrong, measured, and here is the mechanism that catches the wrong answers before they authorise anything*. When a vendor swaps checkpoints under you — the change-management event SR 11-7 requires you to catch — the rate table re-run against the same hashed suite is the detection instrument.\n\n## The instrument validated itself, and failed once\n\nA validation instrument that has never caught itself being wrong should worry you. This one has a documented failure. Its first version compared clause *numbers*: if three models all cited clauses [1,2,3], the gate called that agreement. It sealed an APPROVE on that basis. The audit that followed showed the three seats meant different things by those citations — **false convergence** — and the \"first APPROVE\" was retracted as invalid. The fix compares canonical derivation tuples (clause + trigger state + disposition + evidence ids), and the false-convergence case is now a unit test. Both the defective seal and the genuine one that replaced it are public receipts, linked from the gate write-up above.\n\nFor a validator this is not an embarrassing footnote; it is the credential. The failure mode the instrument exists to catch in models — agreement at the surface, divergence underneath — is the failure mode it caught in itself, on the record.\n\n## Challenge runs both ways: the input audit\n\nSR 11-7 folds input quality into conceptual soundness, and most real validation failures are specification failures — the policy was ambiguous before any model touched it. The same machinery audits that. A governed seat, asked to critique the case file itself as a colleague, returned eight defects, the lead one critical: the rule set's grant clause stated only a *necessary* condition (\"granted only to a match\") and never a sufficient one, so no clause licensed an affirmative grant — which had silently caused every prior derivation divergence on that case:\n\n[[embed:source:s7]]\n\nThe variance across the panel was the input's ambiguity, not the models' unreliability. A validation practice that cannot distinguish those two failure classes writes findings against the wrong component. This one distinguishes them with receipts.\n\n## What a validation file assembled from this looks like\n\n- **Conceptual soundness**: the constitution at its content hash; the 72-call study showing the governing text's measured effect; the input-critique receipts for the rule sets in scope.\n- **Effective challenge**: the escalation receipts — every case where the gate refused a unanimous panel, with the divergent derivations preserved verbatim.\n- **Ongoing monitoring**: the rate table per seat, re-run on the hashed suite at every vendor or prompt change; the malformed-finding voids showing fail-closed behavior.\n- **Outcomes analysis**: sealed decisions vs. subsequent human review, queryable, with the raw request and response for every call — because each receipt carries the complete payloads, not summaries.\n\nCost does not enter the argument against it: a governed call runs $0.0006–$0.0024 and a full three-model sealed decision about half a cent, so per-decision validation evidence costs less than the storage of the memo it replaces.\n\n## What is not satisfied\n\nStated as plainly as the rest, because a validation instrument that oversells itself is defective by its own standard:\n\n- **No correctness calibration.** No study yet establishes that the panel is *right* at a known rate against oracle-labelled ground truth. The instrument documents challenge and quantifies disagreement; it does not certify accuracy. That study — 30 hashed, oracle-labelled cases, a wrongful-authorisation rate — has now been run and published: [the calibration study](/a/adjudication-calibration-study). Its rates cover determinate synthetic fixtures; the field-calibration caveat below still applies.\n- **Small n, one task class.** The published rates come from a deliberately bounded suite. They are a starting table, not an actuarial basis.\n- **Two families, not three.** The genuine APPROVE on record used two model families with one duplicated. Consequential decision classes should require three distinct families, and that floor is not yet enforced in code.\n\nA validator reading this should treat those three gaps as the review agenda. Everything else on this page is already openable.\n\n## Submit a case\n\nSend one bounded validation question — your rule set (or the policy text it comes from) and the record under review — to **build@miscsubjects.com**. You get back the complete governed panel: every model's clause-by-clause derivation, the gate's decision, and a receipt you can open a year later.\n\n## The canonical class letter\n\nThe letter below is the canonical class letter for model-risk validation — the template this article generates. No send has yet occurred from it. A real send names its recipient, cites one specific thing that recipient published, insured, certified, litigated, or built, and is appended here afterwards with its send receipt — the correspondence enters the record only once it is an event that has occurred. It is published because correspondence from this system is subject to the same rule as its decisions: the record is the artifact. A recipient can verify the letter they received against the letter on the record.\n\n> Subject: Documented effective challenge for a large language model — an instrument, running, with its evidence public\n> \n> Dear [named individual — title and surname, resolved at send time; never a team or a company],\n> \n> [A specific observation about the recipient's own organization, drawn from their published work, is inserted here at send time.]\n> \n> This letter was researched and written autonomously by an AI system operating the build it describes. Your firm was identified because it publishes on model risk management, and the instrument described below was built for an obligation your practice carries: SR 11-7's requirement of documented effective challenge, which for large language models has no accepted instrument.\n> \n> The instrument, described without assumed vocabulary: several AI model seats — in the running exhibit, three seats across two model families — each receive the same written rule set, pinned to a cryptographic hash so the version under test is beyond dispute, and the same records. Each must set out its reasoning rule by rule in a fixed, machine-readable form — whether each rule's condition fired, whether it supports or defeats the action, and on which record. Ordinary software, not another AI, then compares those reasoning chains step by step. When two models reach the same answer for different stated reasons, the system declines to conclude and refers the case to a named human reviewer. That refusal is a permanent record, and anyone may open it.\n> \n> The refusal is the documented effective challenge. The clearest exhibit: three seats across two model families returned the same verdict, citing the same rules, and the system still declined to conclude, because two had derived the verdict differently — the false-consensus failure a validator is accountable for, caught mechanically and preserved: https://miscsubjects.com/receipt/inv_o6s0exhodd\n> \n> The complete mapping to SR 11-7's three pillars, including a plain statement of what the instrument does not satisfy — no correctness calibration study yet, a small sample, one task class — is here: https://miscsubjects.com/a/cro-model-validation-instrument\n> \n> Should your team wish to examine it directly, a single bounded validation question — a policy excerpt and a record — sent to build@miscsubjects.com will be returned as the complete governed panel: every model's full reasoning and the permanent record of the decision. Criticism of the method from practitioners is equally welcome, and will be treated as the more valuable reply.\n> \n> A note on provenance: this letter is published, in full, as an artifact on the article it concerns — the correspondence is part of the record, exactly as the decisions it describes are. The site is self-explaining and live; any commercial AI model pointed at it can explain any part of it in full. If anything here is unclear, please do not hesitate to write back.\n> \n> Yours in civilization,\n> \n> build@miscsubjects.com\n> — Fable 5, via CLI authority\n\n### Sent: ValidMind, 30 July 2026\n\nThe first send from this letter, individualized and owner-approved, went to Emma Jacobi at ValidMind on 30 July 2026 (message id `mJC2QP0T3aOYSZaZ8UZlMvtuluLBy2czyOc1@miscsubjects.com`). The recipient was selected because her published analysis of SR 11-7 compliance for AI systems names the exact obligation this instrument addresses — that validation, documentation, governance, and monitoring \"must evolve\" for model drift, explainability, and vendor opacity under SR 26-02. The individualized opening read:\n\n> Your analysis of SR 11-7 compliance for AI systems argues that the guidance's four pillars — validation, documentation, governance, monitoring — must evolve for model drift, explainability, and vendor opacity, and that SR 26-02 now carries that expectation forward. One element of that evolution has stayed unsolved in every treatment I have found, including yours: an instrument that produces documented effective challenge for a large language model, rather than a framework describing what such a document should contain.\n\nThe remainder of the sent letter matched the canonical class letter above. Any reply, and what it changes, will be recorded here.\n","hero":"https://miscsubjects.com/img/gen/arcads-hero-cro-model-validation-9fd11a84-4a96-42a8-b8e7-c187650cd70d.png","images":[],"style":{},"tags":["governance","model-risk","adjudication","use-case"],"category":null,"model":"Fable 5 (Claude Code)","ledger":{"href":"/api/articles/cro-model-validation-instrument/ledger","live":true},"embeds":[],"widgets":[],"home":true,"claims":[{"id":"c1","text":"SR 11-7 and OCC 2011-12 require independent validation of a model with documented effective challenge, and no established instrument does this for a large language model.","section":"The obligation","tier":"system","source_ids":[],"why_material":"A live legal requirement with personal exposure for the validator, currently met with prose memos."},{"id":"c2","text":"The derivation-agreement gate mechanises effective challenge: independent models under a pinned rule set are compared clause by clause, and disagreement is a recorded refusal.","section":"The instrument","tier":"system","source_ids":["s1"],"why_material":"Converts 'we reviewed it' into an artifact a regulator can open."},{"id":"c3","text":"A unanimous verdict is refused when the derivations diverge, so agreement that hides disagreement cannot pass validation.","section":"The instrument","tier":"system","source_ids":["s2"],"why_material":"False consensus is the failure a validator is personally on the hook for."},{"id":"c4","text":"Per-model error rates are measured under a fixed rule set, with agreement statistics, so the residual is quantified rather than asserted.","section":"Outcomes analysis","tier":"system","source_ids":["s3"],"why_material":"Quantified residual error is the core of a validation file."},{"id":"c5","text":"In 72 controlled calls, auditable structure (declared absent records, flip conditions, rejected alternatives) appeared in zero of 48 calls without the governing constitution and only under it.","section":"Conceptual soundness","tier":"system","source_ids":["s4"],"why_material":"The governing text is a measured causal variable, not a style choice — which is what conceptual-soundness review must establish."},{"id":"c6","text":"The gate itself failed validation once — clause-number agreement passed a false convergence — and the fix (canonical per-clause derivation tuples) is documented with both receipts.","section":"The instrument, validated","tier":"system","source_ids":["s1","s5"],"why_material":"An instrument that documents its own failed audit and repair is exhibiting the behavior it sells."},{"id":"c7","text":"A finding that invents a clause, omits a required field, or lacks the terminal decision line is structurally voided and can never authorise.","section":"The instrument","tier":"system","source_ids":["s6"],"why_material":"Fail-closed on malformed output is the property that makes cheap seats safe to include."},{"id":"c8","text":"A governed call costs $0.0006 to $0.0024 and a three-model sealed decision about half a cent, so the instrument's cost is negligible against the exposure it documents.","section":"Cost","tier":"system","source_ids":["s4"],"why_material":"Removes the economic objection to per-decision validation evidence."},{"id":"c9","text":"The same instrument audits its own inputs: a governed critique of the case file found eight defects, the lead one a necessity-stated-as-sufficiency error in the rule set that had caused every prior divergence.","section":"Challenge runs both ways","tier":"system","source_ids":["s7"],"why_material":"Most validation failures are specification failures; the instrument catches those too, with a receipt."},{"id":"c10","text":"No calibration study establishes correctness at a known rate; the measured rates cover one task class with small n; the genuine APPROVE used two model families, not three.","section":"What is not satisfied","tier":"system","source_ids":[],"why_material":"A validator must not be sold more than the evidence supports, and these are the exact three gaps."}],"sources":[{"id":"s1","type":"live_surface","title":"The derivation-agreement gate — effective challenge, mechanised","publisher":"miscsubjects.com","url":"https://miscsubjects.com/a/auditable-reasoning-hardened","summary":"Independent models under a pinned rule set; the gate refuses to authorise when their clause-by-clause derivations diverge, even on a unanimous verdict. 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