llm-vendor-evidence-review

name	llm-vendor-evidence-review
description	Reviews a foundation-model vendor's published evidence pack (system card, model card, evaluation reports, red-team summaries, security and privacy attestations, responsible-use policies, trust-and-safety pages) against firm criteria for the firm's deployment context. Produces a sufficiency view, named gaps with supplemental evidence requested, residual reliance with caveats, recommended owner actions, and re-review triggers. The artefact a model risk lead, AI risk committee, or vendor-diligence officer uses to decide whether to depend on a foundation model in scope. The model-evidence layer that pairs with vendor-diligence in third-party-operational-resilience for the entity-level wrapper. Best for: - A new foundation-model vendor is being onboarded for one or more in-scope use cases and the model-evidence layer is needed for the deployment-context decision. - A foundation-model provider has published a new system card, model variant, or version and the firm needs the delta review. - A periodic re-attestation cycle requires updated evidence-pack review for in-flight vendor models. - An upstream vendor-diligence record has set eval_evidence_status to deferred-to-evidence-review and chained the model-evidence question over. Not the right tool when: - The work is entity-level vendor diligence (financial health, security attestations as entity-level evidence, contract terms, exit posture, sub-contractor footprint). Use vendor-diligence in third-party-operational-resilience. - The vendor model is in-house or open-source with no published vendor evidence pack (the deep work is internal validation under validation-plan). - The work is the deployment-level pre-prod gate; this skill feeds genai-pre-prod-review. - The work is the focused prompt-injection deep-dive on the deployed system (use prompt-injection-risk).
argument-hint	[vendor, model, version, deployment form, in-firm use case IDs, evidence pack scope, or pointer to upstream vendor-diligence record where eval_evidence_status = deferred-to-evidence-review]

LLM vendor evidence review

The work this skill produces is the second-line read of a foundation-model vendor's published evidence against the firm's deployment context. The pack on the table is typically a system card, a model card for the specific variant, evaluation reports, a red-team summary, security and privacy attestations under NDA, the vendor's responsible-use and acceptable-use policy, the trust-centre page on data handling and abuse monitoring, and the vendor's incident-disclosure history. The output is a sufficiency view by criterion, named gaps with supplemental evidence requested, the residual reliance the firm is taking with named caveats, recommended owner actions, and the named events that trigger a re-review.

This is the model-evidence layer. It pairs with the entity-level layer in vendor-diligence (third-party-operational-resilience): vendor-diligence handles financial health, contracts, exit posture, sub-contractor footprint, and entity-level security attestations as entity evidence; this skill goes deep on whether the vendor's published evidence about the model itself is sufficient for the firm's deployment context. The chain is one-directional: vendor-diligence runs first, sets eval_evidence_status = deferred-to-evidence-review where the question is "is the vendor's published evidence pack sufficient for our deployment context", and links to this skill's record by ID. This skill closes the loop with linked_vendor_diligence_id. Neither side restates the other.

The audience reads from three angles at once. The AI Governance Lead owns the artefact and consolidates the analysis. The model risk function (MRMO) co-reviews where the firm's model risk programme treats the use case as in scope, and is the primary co-attestor in bank-affiliated entities. The vendor-diligence officer or head of TPRM consumes the structured record back into the entity-level vendor record. The CISO function co-reviews the security and privacy criteria for any deployment with a cyber overlay (which is most GenAI deployments). The chief privacy officer co-reviews where regulated personal data flows to vendor-side processing. The CCO co-reviews where the use case touches consumer-facing communications, recommendation, or decisioning.

The review is a draft until the named reviewers attest. The skill stops at the recommendation.

Ask first

Most of what the review needs is on the table by the time someone reaches for this skill. A few things to settle before drafting:

• What is the deployment form. Hosted-API, open-weights-self-hosted, open-weights-vendor-hosted, on-prem-appliance, or fine-tuned-derivative. The form rewires the evidence-ask: an open-weights model the firm runs on its own infrastructure has security and privacy posture as firm-side, not vendor-side; a hosted-API model has them as live vendor evidence-asks. Get this on the table first; it sets the rest of the spine.

• What is the in-firm deployment context. The use cases in scope, the architecture (foundation-model only, RAG, tool use, multi-agent, persistent memory, multimodal), and the model-card record from model-card-builder if it has run. The basis for every sufficiency-view criterion is what the in-firm use needs, not what the vendor's general claim covers; without the deployment context, the sufficiency view collapses into an inventory.

• What evidence is actually in hand. The pack as it sits today, with confidentiality markers. NDA-bound items can be reviewed but cannot be quoted in artefacts read at lower source posture; flag the confidentiality on every entry and respect it downstream.

• Who co-reviews and attests. The named co-attestors flow from the loaded sector overlay and cross-cutting overlays: MRMO for banking, chief privacy officer for any regulated-data-touching deployment, CISO function for any cyber-flagged review, CCO for any consumer-facing or decisioning-touching deployment.

When the scope record is supplied, the skill consumes it for institution, persona, source posture, sector and cross-cutting overlays, and the use-case context. Otherwise it asks the practitioner the few facts it needs, and source posture sets what the review can assert at high confidence and what carries [evidence needed].

How the review gets filled in

The review has the same spine across vendors and deployment forms. The order below is the dependency chain a senior practitioner walks; sections without dependencies fill in as evidence arrives.

Deployment form drives evidence-ask scoping; settle it before reading any criterion. The in-firm deployment context drives the basis column on every sufficiency-view entry; it must be in hand before the sufficiency view is filled. The sufficiency view drives the gap list and the residual-reliance read; both depend on it.

Review and vendor-and-model metadata name the reviewer role, review stage (onboarding, version-delta, periodic-reattestation, post-incident, exam-readiness), the vendor and model with version, the deployment form and version-pinning posture, the evidence-pack date, and the in-firm use cases in scope. Where this review chains from vendor-diligence, the linked vendor-diligence ID is recorded; where it chains forward to genai-pre-prod-review or validation-plan, those links populate at the recommended-actions section. Reviewer roles are functions, never named individuals.

Evidence inventory lists the documents reviewed with date, source URL where public, and confidentiality marker. The vendor-self-attestation flag distinguishes vendor-authored documents (system card, model card, vendor red-team summary, vendor responsible-use policy) from third-party attestations (SOC 2 by named auditor, ISO certificate). The distinction carries forward to confidence labelling in the source trace; vendor-authored documents default to vendor-self-attestation confidence and never collapse to high. Confidentiality is required on every entry; NDA-bound items are flagged and respected downstream.

Sufficiency view by criterion is where the review earns its keep. Each criterion gets a status (sufficient, partial, insufficient, missing, not-applicable) and a basis that names what the in-firm use needs and how the vendor evidence reads against that need. The criteria set covers intended-use scope, training-data posture, evaluation coverage, dangerous-capability evaluations, red-team coverage, security posture, privacy posture, content provenance, incident-disclosure history, support and escalation, regulator-engagement history, change and version control, responsible-use policy, and abuse-monitoring and data retention. The basis column is the load-bearing one: a general-purpose hallucination evaluation is not the same as performance on the firm's domain; a vendor red-team on direct injection is not the same as coverage of indirect injection over the firm's RAG corpora. Criteria not applicable to the deployment form are explicit "not-applicable" with the basis (security posture is not-applicable for open-weights-self-hosted because the firm controls the serving plane; the firm-side responsibility shift is recorded), not omitted.

Named gaps turn partial and insufficient sufficiency-view entries into actionable items. Each gap has a criterion link, a concrete description, severity, the supplemental evidence requested, the function-level owner, and a deadline. A gap marked "accepted-as-best-available" is one where the firm acknowledges the residual is unfillable (typical for open-weights training-data disclosure, typical for content-provenance where the vendor does not yet provide watermarking) and absorbs the residual in the residual-reliance section.

Residual reliance is the section that distinguishes a review from an inventory. For each item the firm is depending on the vendor for, the section names the reliance, the scoping caveat that limits it, and the function-level owner who has accepted it. "Firm relies on vendor's published refusal-rate posture for the assistant's intended-use scope; caveat is firm-side in-flight monitoring; accepted by AI Governance Lead" is the shape. Anything left implicit becomes a gap when an incident reframes the question.

Recommended owner actions carry each gap to a function-level owner with a deadline and a severity. Critical-severity items typically block deployment until closed. Where the action requires vendor input, the firm-side owner role is named and the vendor request is the action content; the vendor is not the owner.

Re-review triggers name the events that require this review to be re-run. At minimum, for hosted-API and vendor-hosted forms: vendor model-version swap; vendor new-system-card publication; vendor-disclosed incident affecting the model variant; vendor change to acceptable-use or responsible-use policy; vendor change to abuse-monitoring or data-retention default; expansion of in-firm deployment context (new RAG corpora, expanded tool inventory, new use case). Loaded sector and cross-cutting overlays append their named triggers.

Source trace and confidence records every material claim, its source, the evidence pointer, and a confidence label. Vendor red-team results carry vendor-self-attestation confidence (typically low to medium); third-party attestations from named auditors carry higher confidence. Do not collapse vendor and third-party evidence into one line. Items without evidence carry [evidence needed] and route to recommended actions, not silently into the review body.

Depth flexes with deployment form, tier, and sector. A hosted-API tier-1 review with banking and cyber overlays runs longest. An open-weights-self-hosted tier-2 review compresses the security-posture and privacy-posture sections to "not-applicable" and shifts weight onto the firm-side responsibility shift. Empty named sections are not acceptable, but compression is.

Sector and cross-cutting overlays

When the scope names a sector (banking, insurance, capital-markets, payments-fintech), load the matching references/sector-overlays/<sector>.md. Each overlay carries sector-specific evidence asks, co-reviewer expectations, re-review triggers, and the named additions to the structured-output sector_overlay_notes block. Treating the overlay as background reading is the failure mode; the overlay's named additions land in the review.

The cyber cross-cutting overlay should be considered the default for foundation-model evidence reviews. The threat surface a foundation-model vendor exposes is, in the named regulatory anchors' framing, a cybersecurity risk class; the CISO function co-reviews the security and privacy criteria. The privacy and conduct overlays load when the scope flags them: privacy where regulated personal data may flow to vendor-side processing; conduct where the use case touches consumer-facing communications, recommendation, or decisioning. Climate is not applicable.

Load only the overlays the scope names. Gold-plating with overlays the engagement does not implicate adds noise without challenge value.

Quality bar

The review is only credible when these hold:

• Every material claim cites a source. Unsupported items carry [evidence needed] and route to recommended actions, not silently into the review body.
• The sufficiency view is read against the in-firm deployment context, not against the vendor's general claim. The basis column on every criterion is required.
• Vendor self-attestation is distinguished from third-party attestation. Vendor-authored documents default to vendor-self-attestation confidence; they do not collapse to high.
• Confidentiality is recorded on every evidence-inventory entry. NDA-bound items are not quoted in artefacts read at lower source posture.
• Residual reliance is named with caveats and a function-level accepted owner. Implicit reliance is a gap in waiting.
• Re-review triggers are explicit, not "as needed". For hosted-API and vendor-hosted forms, vendor model-version swap and vendor new-system-card publication are non-optional.
• Owner roles are functions, never named individuals.
• The boundary with vendor-diligence is respected. This skill is the model-evidence layer; entity-level diligence sits in vendor-diligence. The chain is one-directional and the linked record IDs close the loop.
• No fabricated regulatory facts. Unknown section references stay as [verify section] flags in the source-anchors file (not in the review body).
• No named institutions outside finalised public enforcement actions; examples are anonymised and public-source-derived.
• The review is a draft until the named reviewers attest.

Adaptation

Deployment form rewires the evidence-ask scoping. Tier drives depth. Review stage drives which sections lean heavy (onboarding emphasises the full sufficiency view; version-delta focuses on what changed against the prior review and the re-review triggers that fired; post-incident emphasises incident-disclosure history and the linked-incident analysis). Audience drives tone. Sector and cross-cutting overlays load from the scope. Source posture sets what the review can assert at high confidence and what carries [evidence needed]. Where firm-specific policy or taxonomy applies, it lives in references/firm-overlay.md (consumed when present) and never in the review directly.

Output

Default to drafting the review against templates/default-output.md. Render as Word for committee or TPRM forum review, or another format the audience asks for. Produce the structured record at schemas/llm-vendor-evidence-review.schema.json when downstream consumers (genai-pre-prod-review, vendor-diligence, board-ai-risk-pack) need it. The reviewer-attestation block is filled by the named human reviewers (AI Governance Lead with co-attestors per loaded overlays); the review is filed only after.

Downstream consumers: genai-pre-prod-review consumes the structured object for the gate decision (the linked review ID is part of the gate inputs); vendor-diligence consumes the linked record ID and the high-severity gaps and recommended actions back into the entity-level vendor record; board-ai-risk-pack pulls the residual-reliance summary, high-severity gaps, and material re-review triggers; the firm's TPRM forum consumes the review summary as the model-evidence input to the entity-level decision; the AI risk committee consumes the review for any tier-1 deployment. The schema is the input contract for those consumers; additive changes only. Add fields, do not rename or repurpose them.

Pointers

• references/source-anchors.md — citations and excerpts for the named anchors.
• references/sector-overlays/{banking,insurance,capital-markets,payments-fintech}.md — sector overlays loaded from scope.
• references/cross-cutting/{cyber,privacy,conduct}.md — cross-cutting overlays; cyber is the default for GenAI reviews.
• references/firm-overlay.md — firm policy, taxonomy, named owners (consumed when present).
• templates/default-output.md — review template.
• schemas/llm-vendor-evidence-review.schema.json — structured-output contract.
• examples/ — anonymised public-source-derived scenarios (regional bank reviewing a major-vendor hosted-API for a tier-1 KYC assistant; regional life insurer reviewing an open-weights model for a claims-summarisation pilot).
• TROUBLESHOOTING.md — recurring defects.