Testing & Security skills

Use when the user invokes /cr, requests a code review, or before committing to verify correctness, security, and quality of new or modified code in the working tree.

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Browser automation via webctl CLI in Claude.ai containers with authenticated proxy support. Use when users mention webctl, browser automation, Playwright browsing, web scraping, or headless Chrome in container environments.

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Check that a document's claims about code are actually true by reading the prose, the code, and the tests and reporting (or fixing) where they disagree. Use whenever the user wants to verify a README, guide, spec, or docstring still matches the code; whenever they mention documentation drift, doc-code sync, "is this still accurate", stale docs, or keeping docs/tests/code consistent; before publishing or merging a docs change; or as a periodic doc-accuracy sweep. The agent reads the prose's meaning directly — there is no claim-comment DSL to maintain. Pairs with TDD — the test suite is the deterministic behavioral gate, this skill is the semantic prose-vs-reality review.

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Sentence-level and section-level craft for instructions Claude will actually follow, in any container — project instructions, a standalone prompt, or skill body text. Use when the text exists or is being drafted and the question is quality: "why is Claude ignoring this instruction", "rewrite this prompt so it works", "improve my project instructions", "make this instruction stick", "is this too prescriptive", "how much structure does Sonnet need versus Opus". Covers imperative construction, positive framing, strategic-versus-procedural calibration per model, extended thinking, complexity scaling, and a quality checklist. For deciding WHICH container the instruction belongs in, use crafting-instructions. For building, testing and packaging a whole skill directory, use creating-skill.

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Runs a multi-step procedure as a Python DAG, so ordering, branching and retries are enforced by the runner rather than described in prose a model can generate past. Use for "run these steps in order and retry the flaky one until the check passes", "build a pipeline that fetches, validates, then skips the upload when nothing changed", "make sure these steps cannot be skipped", "resume from where it broke instead of redoing the expensive early stages", "run these independent calls at once and merge the results", or any procedure of 3+ steps with branches, input contracts, or side effects that must not block the critical path. Primitives are depends_on, when=, validate=, retry_until=, detached= and journal_path=. Not for a single sequential call, for steps needing reasoning between them that no predicate captures, or for async and distributed work. To audit whether one verification check can actually go red, use gating. To fan work out across many subagents, use a dynamic workflow.

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Build and audit deterministic verification gates — a check that blocks a pipeline and can be shown to go red. Use when writing a calibration gate, CI check, validation script or pre-publication check for a numeric or empirical result; when a plausible-but-wrong value would survive review; when asking whether an existing test, linter rule or check could actually fail; and when a suite passes first try, passes suspiciously often, or was written by whatever produced the thing it checks. Triggers on "can this check fail", "known-bad", "negative control", "calibration gate", "sanity check my results", "is this test actually testing anything".

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Break out of a locked problem frame by picking one disciplined move — reframe, provocation (Po), random stimulus, SCAMPER, inversion, structured analogy, constraint play, or family traversal — and committing to it before evaluating. Use when stuck, when options feel narrow or obvious, when iterations produce variations of the same idea, or when the user says "widen this", "break out of", "think differently", "I'm stuck", "feels too obvious", "stress-test the framing", "what am I missing", or holds two related examples and asks what lies between or beyond them. Complements challenging (which evaluates) and convening-experts (which synthesizes viewpoints); this skill generates distance, not judgment.

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Chooses the right FORMAT for instructions on Claude.ai — project instructions, a skill, or a standalone prompt — and gives the format-specific structure once chosen. Use when the question is which container an instruction belongs in ("should this be a skill or project instructions", "where do I put this", "how do I set up this project", "is this worth a skill"), or when someone has instructions and does not know how to package them. For the writing principles that apply inside any of the three formats, use writing-instructions. For building, testing and packaging a complete skill directory, use creating-skill.

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Find tests that enumerate a domain by copying it, and declare the invariants a codebase depends on. Reports where a parametrize list, for-loop, or it.each iterates a hand-written subset of a dict/set/tuple/Enum that exists in the source, and names the members nothing covers. Use when reviewing tests, when a module gains a name-to-thing table, registry, enum, or dispatch map, before trusting a green suite as evidence a domain is covered, or when asked "is this test actually total", "does anything cover X", "what does this repo guarantee", "which invariants do we declare". Also for vacuous tests that pass over an empty collection, for a domain that has silently NARROWED (an enumeration cannot see that), and for recording the refutation that proves a claim can fail.

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Generate Foundry unit tests for a contract using this repository's conventions, structure, and naming. Use when the user asks for unit tests, Foundry tests, concrete tests, or fuzz tests.

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Generate Foundry smoke tests that validate deployment health using DeployManager/Resolver against real on-chain state with pending governance applied. Use when the user asks for smoke tests, deployment verification tests, or post-deploy health checks.

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Reorganize Foundry test files (*.t.sol) for readability and consistency without changing semantics. Use when the user asks to organize, reorder, clean up, tidy, or reformat a test file's structure.

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Generate Foundry fork tests for contracts that need real on-chain integration coverage. Use when the user asks for fork tests, mainnet or chain fork coverage, or integration tests against live protocol state.

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Use when an AI agent (or any external script) needs to play-test a running Pixi'VN game end-to-end in a real browser — starting the game, advancing/branching the story, answering input prompts, going back, and reading/writing storage — via `Game.testing`, the opt-in devtools bridge exposed on `window`. Load this before wiring up automated/agent-driven playtesting, not for authoring story content itself (see `pixi-vn-narration`).

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Use this skill when adding authentication, handling user input, working with secrets, creating API endpoints, or implementing payment/sensitive features. Provides comprehensive security checklist and patterns.

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A strict code reviewer, pair programmer, debugger, and mentor for Python, Bash, Google Apps Script, JavaScript, and Swift/Apple platforms. Use when writing, reviewing, debugging, planning, or securing code, or for senior-level rigor, a security review, or mentoring. Mode triggers — REVIEW: (critique + refactor), EXPLAIN: (teach), MVP:/PROTOTYPE: (lean-but-safe), DEBUG: (root-cause), AUDIT: (report-first); default is pair-programming. Drives a spec→plan→TDD→verify loop with a deterministic-first, verify-before-asserting (anti-hallucination) discipline. Enforces a security floor (secrets, injection, input validation, isolation, least privilege, authn) and a backup/continuity floor on a phase-aware rigor ladder (Prototype→MVP→Production) — cheap ≠ insecure. Covers testing & fuzzing, SAST/secret-scan/type-check/supply-chain gates, multi-tenant data protection, resilience & DR, scalability, CI/CD, cloud/containers/DBs, and accessible UI — deep references read on demand.

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Run changed e2e flows for a pull request and note the result. Attach video proof only if user explicitly asks for it

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Add beta testers for Pixy on Android and iOS. Use when a user asks to test a new version.

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Verifies that the skill system is working correctly.

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Validez la qualité de vos vidéos IA avant publication avec une checklist complète couvrant technique, créatif, et positionnement marque. Use when: **Avant publication** - Dernière validation avant mise en ligne; **Revue client** - Préparer les points de feedback anticipés; **Itération qualité** - Identifier les problèmes à corriger; **Go/No-Go decision** - Décider si la vidéo est prête; **Post-mortem** - Analyser pourquoi une vidéo a (ou n'a pas) performé

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Test if your solution actually solves the validated problem before building the full product. Master the art of showing concepts and prototypes to get honest feedback on solution fit. Use when: **After problem interviews** to test if your solution addresses validated problems; **Before building MVP** to validate core value proposition; **Prototype testing** to get feedback on concepts and mockups; **Feature validation** to test if new features solve real problems; **Pivoting** to test alterna...

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Test willingness to pay before launching with proven pricing research methodologies. Combine Van Westendorp, Gabor-Granger, and behavioral techniques to find your optimal price point. Use when: **After solution validation** to test willingness to pay; **Before launch** to set initial pricing; **Pricing changes** to test new price points; **New segments** to understand price sensitivity by segment; **Competitive positioning** to price against alternatives

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Extract honest customer insights by asking questions about their life instead of your idea. Master Rob Fitzpatrick's methodology for conversations that can't lie to you. Use when: **Before building anything** to validate if the problem is real and painful; **Customer discovery calls** to get honest feedback without leading questions; **Pivoting decisions** to understand if you should change direction; **Feature prioritization** to learn what customers actually need vs. say they want; **Pricin...

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Document your business model on one page and systematically de-risk it. Master Ash Maurya's adaptation of Business Model Canvas optimized for startups and uncertainty. Use when: **Starting a new venture** to articulate and test your business model; **Preparing for customer discovery** to document hypotheses to validate; **Pivoting decisions** to compare alternative business models; **Investor conversations** to communicate your model concisely; **Team alignment** to get everyone on the same page

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