「claim」の検索結果

Use whenever writing a PR title/description, a commit message body, a code review comment, or an issue — in Hedgehog's own repo or any consuming project. Triggers on "open a PR", "write the PR description", "comment on this PR", "file an issue". Covers writing style (terse, info-dense, Simplified Technical English), the Why/What shape, folding deep reasoning under `<details>`, and the pre-open checklist (CI status, scope, verified claims only).

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。

Independent LLM judge evaluates task completion separately from the executing agent, catching false success claims by reviewing task goal, actions taken, final state, and evidence. Produces PASS/FAIL with confidence score and reasoning.

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。

Remove the git worktrees open-pr review checked PR code out into, each a full checkout on disk. Use when reclaiming disk space after reviews. Asks first; takes no 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。

Hunt JSON Web Token (JWT) vulnerabilities — alg=none bypass, RS256→HS256 key confusion, weak HMAC secret cracking, kid path traversal, JWKS injection, jku/x5u header attacks, embedded JWK confusion, expired-token acceptance, claim mutability, and token replay. Use when an app uses JWT for authentication or stateless sessions.

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。

Hunt OAuth 2.0 and OIDC flaws — redirect_uri abuse, state CSRF, PKCE bypass, scope manipulation, implicit-flow token theft, postMessage origin tricks, ID token sub claim swap, JWKS confusion, response_type confusion, and OAuth-CSRF. Use when an app has Google/GitHub/Facebook/Apple/custom OAuth or OpenID Connect.

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 before EZ_math_model declares quality_audit, packaging, or final delivery complete, especially when pass/fail claims must be backed by files, commands, counts, or concrete evidence.

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。

Health-check the project knowledge base. Looks for contradictions between files, stale claims that newer sources have superseded, orphan files with no inbound cross-references, important concepts mentioned but lacking their own page, missing cross-references, and data gaps. Returns a structured report; does not auto-fix.

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。

Deep research with cross-verification and source tiering. Use when investigating technologies, comparing tools, fact-checking claims, evaluating architectures, or any task requiring verified information. Triggers on "조사해줘", "리서치", "research", "investigate", "fact-check", "비교 분석", "검증해줘".

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。

Turn product photos and a minimal brief into verified, platform-adapted e-commerce detail-page systems, including product fact review, visual analysis, localized copy, 6-10 module story planning, policy-aware text-free image generation or real-photo routing, deterministic Pillow typography, platform-sized slices, long-page previews, manifests, and automated validation. Supports 淘宝/天猫/京东/拼多多/抖音/小红书/Amazon/AliExpress/Temu/TikTok Shop/eBay/Etsy/Shopify. Use when a user asks for 电商详情页, 商品详情图, 商详设计, A+ content, listing galleries, or a short-input workflow that turns product photos into ready-to-review commerce assets without inventing unsupported claims.

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。

Analyze credential-free public website monitoring evidence from server access logs, HTTP fetches, robots/llms/sitemap checks, and exported summaries while protecting raw IP and private query data. Use this skill when the user asks whether crawlers or AI bots reached a site, whether public SEO/LLM discovery files respond, or how to separate observed facts from unknown Search Console, rank, analytics, or citation claims.

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。

Plan and record evidence-backed LLM and AI-search citation checks across approved assistant/search surfaces with timestamped queries, locales, modes, cited URLs, snippets, screenshots or transcripts, and caveats. Use this skill when the user asks whether ChatGPT, Perplexity, Claude, Gemini, Copilot, or another assistant cites a target site, but do not claim citation without direct evidence.

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。

Validate SEO and LLM-readability claims against live HTML, local fixtures, and generated artifacts. Use this skill when the user asks to prove whether title, meta description, canonical, hreflang, JSON-LD, NewsArticle.image, OpenGraph, Twitter cards, RSS autodiscovery, robots.txt, llms.txt, sitemap, news-sitemap, crawler access, or performance evidence is actually present, and when subjective audits must become timestamped pass/fail reports.

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 a command, adapter, or runtime smoke depends on proving an agent runtime's capabilities before trusting command routing, writes, shell access, or validation claims.

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 sources need to be converted into a claim ledger with confidence levels.

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。

診斷並清理 macOS 磁碟空間，特別是「系統資料 / System Data」這類看不出內容的用量。涵蓋開發者工具殘骸（Xcode iOS DeviceSupport、Simulator runtime、DerivedData）、套件管理器快取（Homebrew、pnpm、pip、npm、cargo、go、uv）、容器與 VM 磁碟（Docker、podman、lima）、瀏覽器 profile、以及已移除 app 的孤兒 container。使用時機：(1) 使用者說磁碟快滿了、System Data 佔太多、想清空間 (2) 詢問某個資料夾或快取能不能刪 (3) 移除 app 後想清乾淨殘留檔案、完整解除安裝 (4) 想知道 Docker.raw、Group Containers、Library/Caches 這些是什麼、佔了多少。Also triggers in English — disk full, startup disk almost full, free up disk space, clean up Mac storage, what is System Data on my Mac, what is taking up space, safe to delete this cache, uninstall app leftovers, reclaim disk space, Docker.raw huge, Xcode taking too much space

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。

Apply WIT (Writing Is Thinking) as a human–LLM collaborative scientific reasoning skill for scientific question formulation, finding-driven research planning, next-experiment selection, Results or Discussion review, claim–evidence and reviewer stress tests, manuscript logic audits, deadline closure, and researcher growth. Use when the user invokes WIT or asks for these question-driven scientific reasoning workflows; do not use for generic copyediting, summarization, or literature search alone.

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 RuField tests, trust boundaries, privacy projections, and evidence promotion. Use for conformance review, security regression review, release validation, or checking whether field accuracy claims have support.

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 and execute approved research Experiment, Tuning, or Design Cards with reproducible logs, metrics, environment, and artifacts. Use for bounded coding, debugging, and runs; not for changing claims, priorities, budgets, or the Research Spine.

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。

Direct a claim-driven research experiment project from post-Idea intake through method realization, prioritized evidence collection, Human Gates, and Evidence Freeze. Use for scientific planning, state transitions, queues, budgets, or recovery; not for running code or independently auditing results.

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。

Validate and scientifically interpret completed research runs, including negative, null, boundary, confounded, failed, and inconclusive outcomes. Use after execution to assess evidence and claim impact; not to edit methods or schedule experiments.

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 recent high-relevance papers from a target venue to identify claim-relevant experimental evidence gaps after core P0 results exist. Use for venue completeness and reviewer-risk analysis; not for redefining the research question or running experiments.

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。

Produce a visible, evidence-backed privacy and security report for a local iOS app by scanning permission declarations, network code, dependencies, persistence, and risky APIs, while complementing the official Claude Code security-guidance plugin. Use after implementation, in a live security lane, or before claiming that an app is offline and account-free.

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。

Conduct a peer review of research methodology, experimental design, and manuscript quality. Covers methodology evaluation, statistical appropriateness, reproducibility assessment, bias identification, and constructive feedback. Use when reviewing a manuscript, preprint, or internal research report, evaluating a research proposal or study protocol, assessing evidence quality behind a claim, or reviewing a thesis chapter or dissertation section.

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。

Identify gemstones using optical properties, physical tests, and inclusion analysis. Covers refractive index, specific gravity, pleochroism, spectroscopy indicators, and common simulant detection. Use when identifying an unknown gemstone, verifying a seller's claim about species identity, distinguishing natural stones from simulants or synthetics, building gemological literacy through structured observation, or identifying rough material before cutting to ensure safe handling.

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。