「audit」の検索結果

Use when a website needs a broad audit covering UX, conversion, content, SEO, technical correctness, and information hierarchy before changes are planned.

日本語の概要は準備中です。原文の説明を表示しています。

Sets up safe working habits and a change log so you always know what Cowork has done to your files — and can undo anything. Use when setting up file protection guardrails, for establishing safe automation habits, during initial access configuration, when granting file permissions for the first time, or when the user says "is cowork safe", "file safety", "what if it deletes my files", "audit trail", "safety setup", "I'm nervous about file access", "how do I trust cowork with my files", "can cowork mess up my computer", "I heard someone lost files", or "how do I stay in control".

日本語の概要は準備中です。原文の説明を表示しています。

Audits your Cowork setup across five categories, scores each one, and gives you a prioritized improvement plan. For reviewing how well you are using Cowork, when optimizing your workspace configuration, or during a quarterly productivity review. Use when the user says "health check", "am I using cowork right", "optimize my setup", "cowork audit", "what am I missing", "is my setup good", or "how do I get more out of cowork".

日本語の概要は準備中です。原文の説明を表示しています。

Perform critical Rust code reviews covering correctness, edition 2024 compliance, error handling, API design, async pitfalls, and dependency hygiene. ALWAYS use this skill when the user wants to review, audit, or critically evaluate Rust code — whether that's a PR diff, a specific crate or module, a cross-cutting concern like error handling, or the whole codebase. This includes requests to "review my changes", "check this code", "audit for best practices", "look for issues", "what's wrong with this", or "flag anything that could bite us". Use it even when the user doesn't say "review" explicitly but is asking you to find problems, inconsistencies, or anti-patterns in existing Rust code. Do NOT use for requests to write, fix, refactor, test, explain, or implement code — only for evaluating existing code.

日本語の概要は準備中です。原文の説明を表示しています。

Validates agent definitions against the Antigravity audit rubric.

日本語の概要は準備中です。原文の説明を表示しています。

Validates agent configurations for model selection, tool permissions, focus areas, and approach quality. Use when reviewing, auditing, improving agents, or learning agent best practices.

日本語の概要は準備中です。原文の説明を表示しています。

"Implement a web crawler pipeline covering URL discovery, fetching, parsing, and storage. Use this skill when the user needs to build a site crawler, audit website structure, or collect web data systematically — even if they say 'scrape a website', 'crawl all pages', or 'site audit spider'.".

日本語の概要は準備中です。原文の説明を表示しています。

Audit dependency freshness — scan outdated deps and CVEs, classify severity, record update/defer/skip decisions in Atrium, gate PASS/WARN/FAIL. Use when checking for outdated packages or deciding whether to upgrade. Trigger on "outdated dependencies", "dependency audit", "are my deps up to date", "should I upgrade".

日本語の概要は準備中です。原文の説明を表示しています。

Design UI, build components, write Playwright E2E tests, run WCAG accessibility audits, and do visual review. Use when building or testing frontend/UI work. Trigger on "build a component", "frontend", "E2E test", "accessibility audit", "a11y", "visual review", "make this look good".

日本語の概要は準備中です。原文の説明を表示しています。

Audit a live website across 7 dimensions — SEO, performance, links, privacy, accessibility, security, content — with PASS/WARN/FAIL gates. Use when checking a deployed site's health or quality. Trigger on "audit my website", "site health", "check SEO", "is my site accessible", "website-health <url>".

日本語の概要は準備中です。原文の説明を表示しています。

Genereert uit een (semi-)gevalideerd regelrecht-corpus een geloofwaardige service-PoC (burger- + behandelaar-portaal, of een headless beslis-service) en zet die in als validatie-instrument met uitvoeringsexperts — om tastbaar te maken wat nodig is om een wet rechtvaardig in de praktijk te brengen, gezien vanuit de betrokkene. Gebruik dit als workshop-fase ná de logica-/scenariovalidatie (audit-products) om de dienstverlening-kant te valideren: welke service impliceert de wet, waar zit menselijk oordeel, welke last ligt bij de burger, welke termijnen, waar is de wet hard of onduidelijk. Dossier-agnostisch; de regelrecht-methode (hooks, legal_character, untranslatables, source/implements, type_spec, receipts) is de vaste taal. Voor de logica-/scenariovalidatie zelf: zie de zusterskill regelrecht-audit-products.

日本語の概要は準備中です。原文の説明を表示しています。

Audits whether a machine-readable regelrecht law model is faithful to the LETTER of the wettekst — and strictly separates the wettekst (leading) from the toelichting (Nota/Memorie van Toelichting; explanatory, not a norm). Runs in critical passes per article/lid and detects four deviation classes: toelichting-bleed (a modeled criterion that the letter only states as an open norm, or not at all), missing verbatim elements (a word/condition such as a "tenzij" or a qualifier dropped from the model), wrong legal_basis anchoring (an endpoint hung on a "kapstok"-article while the operative norm lives elsewhere), and verbatim-drift in text: (an ingetrokken/older redaction). Also detects positief-lid vs uitsluitings-lid conflicts and checks the chapeau for an explicit derogation rule ("zo nodig in afwijking van het eerste lid") before judging precedence. Classifies every finding as modelfout (fix), wettekst-gevolg (report, do not fix), or letter-vs-toelichting-question (jurist decides what is leading + revision signal). Use when the user wants to know if a model is "dicht bij de letter", mentions letter vs toelichting/bedoeling, fidelity, "natuurgetrouw", or before trusting feature outcomes.

日本語の概要は準備中です。原文の説明を表示しています。

Use when planning, drafting, revising, compressing, or auditing conference rebuttals and author responses in OpenReview Markdown or PDF. Supports exact reviewer mapping, evidence and experiment integration, guided risk decisions, venue-format validation, and blind reviewer/AC audits.

日本語の概要は準備中です。原文の説明を表示しています。

Optimizes Atlassian Forge apps to reduce platform consumption and avoid unnecessary costs using Atlassian's "Optimise Forge platform costs" guidance. Use when the user asks to optimize Forge app costs, reduce Forge invocations, lower GB-seconds, reduce storage or log usage, tune memory, replace polling, improve scheduled triggers, reduce KVS writes, move work to the frontend, use bridge APIs, batch API calls, add caching, or evaluate Forge Remote trade-offs. By default, perform an audit first and offer to make the recommended changes after presenting the audit. Only modify files immediately when the user explicitly asks the agent to implement or apply optimizations.

日本語の概要は準備中です。原文の説明を表示しています。

Audit data quality across six DAMA DMBOK dimensions — Completeness, Accuracy, Consistency, Timeliness, Validity, Uniqueness. Produces a scored data quality report with issue log and remediation plan. Use when profiling datasets, onboarding new data sources, or building data quality gates.

日本語の概要は準備中です。原文の説明を表示しています。

Audit a spreadsheet for formula accuracy, errors, and common financial-model mistakes. Use for selected ranges, single sheets, or whole-workbook model checks including balance-sheet balance, cash tie-out, roll-forwards, and logic sanity.

日本語の概要は準備中です。原文の説明を表示しています。

General workflow for auditing ML CI failures, experiment regressions, training run failures, golden metric failures, and telemetry-backed ML work-product claims from local repositories, logs, metrics, configs, and artifacts. Use when Codex needs to decide whether an ML failure is a model/convergence issue, correctness bug, data/config issue, infrastructure/runtime issue, evaluation/gating policy issue, or unsupported claim, and produce structured evidence-backed outputs.

日本語の概要は準備中です。原文の説明を表示しています。

Detect and rewrite AI writing patterns to make content sound authentically human. Supports voice calibration from the author's own writing samples. Use when asked to humanize text, remove AI patterns, calibrate voice, audit content for AI detectability, or check if writing sounds like ChatGPT. Triggers: /humanize, /voice-calibrate, /audit-ai

日本語の概要は準備中です。原文の説明を表示しています。

Drain the Pharos Dependency Map coverage-audit queues into evidence-refreshed edges, reviewed target dispositions, or documented deferrals. Use monthly after weekly production dependency audits, after dependency coverage drops, or when reviewing adapter gaps, material unlinked slices, symbol leads, duplicate/split groups, or unverifiable published edges.

日本語の概要は準備中です。原文の説明を表示しています。

Use for a whole-corpus, read-only audit of tracked stablecoin static metadata and domain sidecars, especially after catalog changes or when factual or internal-consistency drift needs review.

日本語の概要は準備中です。原文の説明を表示しています。

Audit and repair Pharos documentation against the codebase. Use for documentation update passes, verified-doc drift, source-path/doc-sync failures, methodology/doc routing updates, or requests to verify docs without trusting existing prose.

日本語の概要は準備中です。原文の説明を表示しています。

TLS/SSL configuration audit. Tests protocol versions (SSLv2/3, TLS 1.0/1.1/1.2/1.3), cipher strength and ordering, certificate chain validation (intermediates, CT logs, OCSP stapling, pinning), known vulnerabilities (POODLE, BEAST, CRIME, Heartbleed, ROBOT, DROWN, Ticketbleed, GOLDENDOODLE), session management (ticket reuse, resumption, fixation), renegotiation attacks, TLS 1.3-specific issues (0-RTT replay, PSK modes, downgrade), HSTS deep analysis (preload, subdomains, bypass), and certificate revocation (CRL, OCSP responder, stapled response freshness). Compliance-mapped to PCI DSS 4.0 (full Section 4), NIST SP 800-52r2, and FedRAMP. Uses testssl.sh, sslscan, sslyze, openssl, nmap NSE scripts, and nuclei SSL templates. Multi-port scanning across 20+ TLS-bearing services.

日本語の概要は準備中です。原文の説明を表示しています。

Use when auditing GitHub Actions workflows for script injection vulnerabilities via unsanitized context expressions. Trigger on: "github actions injection", "workflow injection", "head_ref injection", "github context injection", "pwn request", "github.head_ref", "github.event.pull_request.title", "github.event.issue.body", pull_request_target workflows, run: steps interpolating GitHub context variables, CI/CD script injection, GitHub Actions security audit.

日本語の概要は準備中です。原文の説明を表示しています。

Canonical entry point for the full Gaia evidence verification pipeline. Invoke as /evidence-verification-pipeline or /ev-pipeline — both names trigger this skill. Use whenever you need to run the evidence phases end-to-end: collecting raw evidence from the data lake, verifying live GitHub star counts, running Phase 2B benchmark-source verification, running adversarial auditing for noise and URL errors, and checking link health via Firecrawl. Also use when someone says "run the evidence pipeline", "verify the evidence lake", "audit evidence", "run ev-pipeline", "full evidence check", "pipeline run", "prepare evidence for ingestion", or "refresh the data lake". This is the pre-ingestion step — run it before importing any evidence into the registry.

日本語の概要は準備中です。原文の説明を表示しています。