Testing & Security skills

Evaluate a single skill's quality against its stated purpose. Classifies the skill's purpose type, then scores applicable quality categories — universal dimensions always apply; structural dimensions (scripts, references, assets) are scored only when warranted by the skill's purpose. A focused 20-line behavioral skill with no bundled resources scores fully on all applicable categories. Use when auditing skill quality, checking marketplace readiness, evaluating skill completeness, performing pre-publication evaluation.

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This skill should be used when the user asks to "validate Perl script", "check Perl syntax", "verify Perl code", "/perl-validate", or mentions script validation, compile check, security review, or best practice compliance for Perl code.

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Audit agent lifecycle — validates agent execution capability against configuration. Accepts plugin path, runs 8 semantic audits (capability vs config alignment, skill loading correctness, inter-agent contracts, prompt contradictions, tool sufficiency, dead agents, scriptable patterns, pattern learning), writes reports to .plugin-creator/audits/. Use when auditing agent lifecycle, checking agent capabilities, verifying tool access, finding dead agents, validating agent contract alignment, or confirming agents can execute workflows.

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Write and evaluate effective Python tests using pytest. Use when writing tests, reviewing test code, debugging test failures, or improving test coverage. Covers test design, fixtures, parameterization, mocking, and async testing.

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Use when building, extending, or debugging FastMCP v4 (or v3) Python MCP servers. Activates on FastMCP tool/resource/prompt creation, provider and transform implementation (CodeMode, Tool Search), auth setup (MultiAuth, PropelAuth, KeycloakProvider), client SDK usage, FastMCPApp and Generative UI server building, fastmcp-slim client-only installs, nginx reverse proxy deployment, Prefab Apps, OTEL observability, testing, and v3→v4 migration. Grounded in official FastMCP v4 docs plus locally-verified v3 gotchas — zero speculation.

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Verify after implementation that a feature achieved its required user/system outcomes. Use for goal-backward post-implementation verification that tests observable behavior rather than merely checking code existence.

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Design validation and maintained regression protection before test authoring. Use for TDD increments, acceptance or regression evidence, test boundary/oracle decisions, and multi-factor interaction coverage.

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Review a code change for correctness-maintainability defects not owned by a narrower security/performance/accessibility perspective. Use for an independent quality perspective on a defined change set.

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This skill should be used when the user asks to write Perl tests, test Perl code, use Test More, run prove, create test suite, mock Perl, or mentions Perl testing, TAP, Test Class, Test Deep, or test-driven development in Perl.

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Review existing tests against the software and contracts they actually exercise. Use to assess whether a test has justified unique protection, detects consequential faults, tolerates valid refactors, earns its lifecycle cost, or deserves strengthening, replacement, consolidation, or removal consideration. Reviews are read-only and evidence-backed, including TDD and regression tests.

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Use when investigating failing tests or deciding whether to change the test or product. Validate test expectations against authoritative intent, trace product and test boundaries, and require evidence for the correction rather than automatic code fixes or test dismissal.

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Trace bugs, CI failures, and unexpected behavior from reproduced evidence to a causal mechanism and governing contract. Distinguish product, architecture, test-oracle, and harness defects; investigate intermittent failures with controlled experiments and report unresolved evidence explicitly.

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Review a change for security defects such as secret exposure, injection, authentication/authorization failures, unsafe deserialization, and dependency risk. Use for an independent security perspective on a defined change set.

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Use when Stage 1 Discovery is complete and design must begin — transforms the ARTIFACT:DISCOVERY into an actionable ARTIFACT:PLAN via RT-ICA prerequisite verification. Produces approach, components, success criteria, acceptance tests, and risks. Blocks on missing prerequisites before design proceeds.

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Use when a diff needs four parallel perspective reviewers (Security, Performance, Quality, Accessibility). Creates an ephemeral SAM plan, collects structured verdicts, synthesizes them into one deduplicated cross-referenced punch list, prints one summary line per perspective, and exits non-zero if any perspective returns REJECT. SKIP is a passing outcome.

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Close a completed GitHub milestone. Args: {milestone-number}. Audits open and closed issues, offers to carry forward open items to a new or existing milestone, closes the GitHub milestone, updates Project V2 Status to Done for closed issues, and generates a completion summary. Use when a sprint or release is finished and needs to be officially closed.

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Analyze the causal system-wide impact of a proposed change across behavior, interfaces, state/data, runtime dependencies, tests, documentation, controls, people/processes, and model/prompt/context behavior. Use before planning when lexical reference search is insufficient to establish blast radius and verification obligations.

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Review test effectiveness against authoritative contracts, relevant fault detection, refactor tolerance, boundary fidelity, isolation, and diagnostic value. Use when auditing test quality, reviewing coverage gaps, improving regression protection, or assessing tests after a change.

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Use when all tasks for a feature are marked COMPLETE — runs holistic quality gates including code review, feature verification, integration check, documentation drift audit and update, and context refinement. Creates follow-up plans when issues are found.

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Local codebase analysis research angle — derives behavioral contracts, coding conventions, SKILL.md flow insertion points, and agent data availability maps from actual source files. Use when the blocking question is answered by reading the repository: what does this function actually do, what pattern does the codebase use for X, where in this workflow does a new step go, or what data does this agent already have.

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Audit documentation claims against implementation and authoritative repository evidence. Use when checking whether README, architecture, configuration, API, usage, or feature documentation is stale, incomplete, contradicted by code, missing implemented behavior, or inconsistent with a normative contract.

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Use when analyzing failing test cases to determine whether failures indicate genuine bugs or test implementation issues. Activates on "analyze failing tests", "debug test failures", "investigate test errors", or when provided with specific failing test names or output. Applies balanced investigative reasoning — does not auto-fix tests without establishing root cause.

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Validate and iterate on the SDLC Layer Separation Architecture implementation across the check categories defined in its Evaluation Checklist — cross-references, doc completeness, knowledge-explorer layer filters, research entry metadata, integration points, and plan consistency. Produces a structured findings report and optionally applies safe fixes. Use when validating a first-pass implementation, before claiming layer work complete, auditing layer docs or schema, or running --dry-run to preview findings without changes.

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Test harness for Claude Code skill argument substitution — demonstrates capture-block pre-declaration, XML tag referencing, unintentional variable corruption in code blocks, and correct placement of shell examples in reference files. Use when verifying substitution behavior before applying a pattern to other skills, testing how arguments flow from skill invocations, or understanding the pre-declaration and reference file pattern with greet/farewell/inspect actions.

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