By anotb
Compliance and controls testing skills for test plans, sampling, evidence requests, workpapers, exception analysis, issue drafting, and QA review.
Designs the sample for a control test before fieldwork starts. Defines the testable population, picks a sampling method (statistical or judgmental), sizes the sample, sets a tolerable deviation rate, names the selection technique, and documents the rationale a reviewer can defend in front of an examiner. Output is a sampling memo that drops into the test plan or workpaper as a referenceable artifact. Best for: - A second-line testing pod or internal-audit team is scoping a control test and needs a defensible sample method, size, and rationale before pulling evidence. - A reviewer is challenging a first-line control owner's self-attested testing because the sampling rationale is missing or thin and the sample needs to be redesigned. - A walkthrough has confirmed control design and the next step is sizing operating-effectiveness testing across a defined population. - A prior-cycle workpaper failed QA on sample-design grounds and the redraft starts at the sampling memo. Not the right tool when: - The control or obligation has not been mapped yet. Run `risk-compliance-core/skills/control-matrix` and come back with a control ID. - The full test plan has not been scoped. Run `test-plan-builder`; this skill produces the sampling section that test-plan-builder consumes by reference. - The evidence ask itself is the work. Run `evidence-request-builder`; sampling sets which items the request targets, but the request artifact is separate. - Exceptions have already been identified and need classification. Run `exception-analysis`. - The completed workpaper is being written. Run `workpaper-drafter`; this skill stops at the sample drawn.
Drafts the provided-by-client (PBC) evidence request list for a single control test cycle: one numbered row per ask, each carrying the control objective tested, criterion source, artifact requested, format, system of record, owner role, due date, population reference, reliance classification, and status. Produced before fieldwork begins; tracked through fieldwork; closed when every row resolves to received-or-not-applicable. The deliverable is an Excel workbook rendered via the `xlsx` skill in `document-skills`. Downstream, the workpaper consumes the request_id per evidence row and the closure binder consumes the closed list as the index of what was produced. Best for: - A compliance-testing or internal-audit pod has a signed test plan and is preparing the evidence ask before fieldwork begins. - A second-line reviewer is preparing for an upcoming examination and needs to pre-anticipate the regulator's evidence asks against current control coverage. - A QA reviewer is building a re-perform request list to redo a workpaper because the original evidence trail was thin. Not the right tool when: - The test scope and procedures have not been written. Use `test-plan-builder` first; this skill consumes the test plan's procedures and criteria. - The sample has not been designed. Use `control-sampling` first where the requests need a sample-ID set; small inline samples can be drafted alongside the request list, large samples sit in a sampling memo this skill references. - Evidence is in hand and the work is documenting test results. Use `workpaper-drafter`. - The work is QAing a completed workpaper for evidence sufficiency. Use `qa-workpaper`. - The work is assembling the evidence index after fieldwork closes. Use `evidence-binder` in `risk-compliance-core` — that skill indexes what was produced; this skill asks for what is needed. The two are different artifacts at different lifecycle points.
Classifies the deviations a control test surfaced into design gaps, operating-effectiveness failures, evidence gaps, scope disagreements, data-integrity issues, and anomalies; ranks severity with rationale; names a root-cause hypothesis; sets disposition (elevate to issue, close at exception, re-test, expand sample); and builds the handoff package downstream issue write-up consumes. Output is an exception register that pairs with the testing workpaper and ladders confirmed exceptions into the issue lifecycle. Best for: - A compliance-testing or internal-audit reviewer has finished sample testing and is sitting on a list of deviations that need to be classified before they become findings. - A QA reviewer is challenging a workpaper's exception treatment because the line between evidence gap and control failure was blurred. - A repeat-issue review needs to confirm whether deviations across testing cycles are the same root cause or coincidental. - A second-line lead is preparing a handoff to issue write-up and wants the criterion, condition, cause, effect, and recommendation seed populated before the writer opens the issue artifact. Not the right tool when: - The test has not been run yet. Pre-fieldwork scoping is `test-plan-builder`; sample design is `control-sampling`; evidence asks are `evidence-request-builder`. - The exception has already been classified and the work is drafting the issue. Use `risk-compliance-core/skills/issue-writeup`; this skill produces the input that issue-writeup consumes via `source_exception_id`. - The work is drafting the workpaper end to end. Use `workpaper-drafter`; that skill consumes the exception register this skill produces via `exception_register_id`. - The work is QA on a completed workpaper. That is `qa-workpaper`.
Reviews a completed control-test workpaper for QA along named dimensions: scope alignment to the test plan, source-criteria sufficiency, evidence reliability, procedure execution rigor, exception classification, conclusion support, severity calibration, reviewer separation, and remediation handoff. Output is a QA review pack — Excel workbook with QA markup tabs over the workpaper plus a Word QA memo summary — that lists deficiencies by severity, a decision (accept, return for rework, conditional accept), and required rework before workpaper closure. Best for: - A second-line QA function or independent reviewer is performing the standard QA pass over a completed workpaper before issue closure or examiner sharing. - An internal-audit director is rolling up workpaper-quality metrics across a testing cycle and needs structured QA notes per workpaper. - A targeted Federal Reserve, OCC, FDIC, CFPB, NYDFS, or state DOI exam is imminent and the team is doing a self-QA sweep on the workpaper population the examiner will likely sample. - A workpaper failed prior QA, was reworked, and needs a post-rework re-QA before closure. Not the right tool when: - The workpaper has not been drafted. Use `workpaper-drafter`. - The test plan itself is being reviewed (design-stage review of `test-plan-builder` output, not QA of a completed workpaper). - Exceptions identified during QA need their own classification. Use `exception-analysis` for the QA-identified deviations from the methodology, not for the original control deviations the workpaper already classified. - The work is drafting an issue from a confirmed finding. Use `risk-compliance-core/skills/issue-writeup`; this skill's deficiency findings on the workpaper are not the same as control issues on the entity.
Drafts the pre-fieldwork test plan for a single control test cycle: scope, control objective, named source criteria, period, population, sampling reference, walkthrough plan, design-effectiveness procedures, operating-effectiveness procedures, evidence-request reference, pass and fail criteria, limitations, downstream consumers, and reviewer sign-off block. Output is the planning artifact that gets reviewer sign-off before evidence pulls and fieldwork begin; it is the contract the workpaper is written against. Best for: - A compliance-testing or internal-audit team is scoping an annual test plan or a one-off targeted review and needs the pre-fieldwork planning workpaper before evidence pulls and fieldwork. - A second-line reviewer is responding to a regulatory-change-management trigger (a new rule, an updated examiner priority, a new exam letter) by standing up a fresh test against an updated control set. - An audit lead is rebuilding a test program after a prior issue, restating control objectives and procedures from first principles before the next cycle starts. Not the right tool when: - The control inventory and risk-to-control mapping has not been done. Run the control-matrix work in `risk-compliance-core` first; the test plan consumes a control ID, it does not invent one. - Sample design is the only thing needed. Use `control-sampling` standalone; the test plan references the sampling memo by ID. - The evidence ask is the only thing needed. Use `evidence-request-builder` standalone; the test plan references the evidence request list by ID. - Fieldwork is in flight or complete. Use `workpaper-drafter` for during and post-fieldwork documentation. Use `qa-workpaper` for review of the completed workpaper. Boundary: this skill is pre-fieldwork; `workpaper-drafter` is during and post; `qa-workpaper` is review of completed work. The three are sequential, not redundant.
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Plugins for second-line and 1.5-line financial-services work. Skills cover what risk and compliance teams (and the advisory practitioners who support them) actually produce: scoping a review, mapping obligations, building a control matrix, drafting a model card, writing up an issue, building a vendor-diligence pack, packaging a risk-committee read, working a SAR / no-SAR file, prepping for a supervisory cycle, and so on. Skills are grounded in regulatory and standards material, with sector context (banking, capital markets, insurance, payments / fintech) loaded conditionally from the scoping record.
Built primarily for Claude (and Claude Code), but the skill files follow the open SKILL.md format and can be loaded into other agentic systems that support it: GPT, Gemini, in-house open-weights deployments, or anything else that reads agent skills. The skills are markdown plus optional schemas; the format is the standard, the work product is what travels.
The repo extends Anthropic's published financial-services plugin family. Where Anthropic's plugins cover the cross-industry first-line baseline (financial analysis, banking deal work, equity research, PE, wealth, fund admin, ops), these go deeper into US second-line and 1.5-line work and US supervisory expectations.
Second-line and 1.5-line practitioners inside regulated firms: model-risk leads (MRMO), AI governance leads, third-party risk managers (TPRM), BSA / AML officers, sanctions officers, compliance heads (CCO), fair-lending and UDAAP review teams, controls testing and internal audit teams, risk reporting and CRO-office teams, regulatory-affairs and regulatory-change teams, operational-resilience leads, fund-board secretaries, disclosure committees.
And the advisory and consulting teams running the same work for those firms.
If you work in 1.5L, 2L, or adjacent functions, the skills let Claude (or other agentic systems supporting the SKILL.md format) draft alongside you, like a colleague who knows the work and defers to your judgement on the call.
references/sector-overlays/<sector>.md inside the relevant capability skill, loaded conditionally from the scoping record.references/source-anchors.md with the regulatory and standards citations they lean on. US-deep, with EU as overlay and UK as see-also.The skill set is public-source-derived and anonymous, with no firm-specific policy baked in.
Standalone agent plugins (one-shot reviewers that orchestrate related skills end-to-end) are not in this release. The next iteration adds a maker / checker loop with genuine context-isolated subagent forking, primary-plus-critic two-agent shape, and plugin dependencies in place of bundled-skill copies. See ROADMAP.md for the target shape.
| Plugin | What it covers |
|---|---|
risk-compliance-core | Scoping, obligation mapping, control matrices, evidence binders, issue write-ups, human-review gates, policy-gap reviews. |
regulatory-change-management | Regulatory impact assessment, rule-to-obligation extraction, policy diffs, implementation plans, exam briefs. |
ai-governance-model-risk | AI use-case intake, AI risk tiering, EU AI Act triage, model cards, validation plans, agentic-AI controls, board AI-risk pack, GenAI deep-dive (prompt injection, RAG eval, pre-prod review, LLM vendor evidence). |
third-party-operational-resilience | Vendor diligence, criticality, contract-gap review, exit plans, concentration, DORA register, severe-but-plausible resilience testing. |
compliance-testing | Test plans, control sampling, evidence requests, exception analysis, workpapers, QA review. |
risk-reporting | Risk committee packs, BCBS 239 self-assessment, KRI commentary, SEC cyber-disclosure readiness, attestation packs, management responses to MRA / MRIA / audit findings. |
financial-crime-governance | CDD review, EDD escalation packs, SAR-decision QA, AML model monitoring, sanctions-screening QA, negative-news triage. |
consumer-compliance-fair-lending | Adverse-action review, fair-lending test plans, UDAAP risk review, Section 1071 readiness, complaint-theme analysis, marketing-claim review. |
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Regulatory change management skills for impact assessment, obligation extraction, policy diffing, implementation planning, and exam brief preparation.
AI governance and model risk skills for AI intake, risk tiering, model cards, validation planning, agentic controls, EU AI Act triage, AI vendor review, and board risk packs.
Third-party risk and operational resilience skills for vendor diligence, criticality assessment, DORA registers, contract gaps, exit plans, resilience testing, and concentration risk.
Core GRC workflow skills for obligation mapping, control matrices, evidence binders, issue write-ups, human-review gates, and policy gap reviews.
npx claudepluginhub anotb/second-line-financial-services --plugin compliance-testingComprehensive skill pack with 66 specialized skills for full-stack developers: 12 language experts (Python, TypeScript, Go, Rust, C++, Swift, Kotlin, C#, PHP, Java, SQL, JavaScript), 10 backend frameworks, 6 frontend/mobile, plus infrastructure, DevOps, security, and testing. Features progressive disclosure architecture for 50% faster loading.
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