「find」の検索結果

Audit whether a paper's EVALUATION DESIGN actually measures what it claims and whether its reporting is complete — the validity layer family D (experiment-forensics) cannot reach. Three patterns: train/test leakage means the reported score may not measure generalization (HP-EVAL-LEAKAGE — adopts the Kapoor & Narayanan 8-type / 3-category leakage taxonomy; the illegitimate-proxy / sampling-bias / pretraining-contamination subtypes hand off as needs_external_check, naming but NEVER running Oren-2023 exchangeability / Shi-2023 Min-K% / Golchin-2023 Time-Travel / BIG-bench canary); a load-bearing LLM judge is conflicted (same model/family as a compared system) or unvalidated (no human-agreement, no bias control) (HP-JUDGE-VALIDITY); a declared condition/metric is dropped or switched to favor the method, or 'best' is chosen with no held-out set (HP-SELECTIVE-REPORTING). Verdict-bearing at L0/L1 from the DESCRIBED protocol — NOT repo-gated like experiment-forensics; L2 only CONFIRMS against split/preprocessing/result files. A fresh cross-model reviewer (gpt-5.6-sol xhigh, read-only, fresh thread per pass) PROPOSES findings, each span-anchored to a ledger claim_id; tools/adjudicate_findings.py DECIDES the verdict. Leakage and under-reporting are usually HONEST methodological errors — every finding describes a discrepancy to CHECK, never an accusation. An LLM generating GROUND-TRUTH labels is HP-FAKE-GT (experiment-forensics) — routed there, not here. Emits eval-design-forensics.findings.json; computes NO verdict. Detect-only. Triggers: "eval design audit", "evaluation validity", "train/test leakage", "data leakage", "is the score measuring generalization", "LLM judge bias", "is the judge validated", "selective reporting", "cherry-picked results", "评估设计审计", "评测有效性", "数据泄漏", "训练测试集泄漏", "裁判模型有没有验证", "选择性报告".

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。

Semantic Python code queries via a stdio LSP client driving pyright-langserver. Provides binding-resolved go-to-definition, find-references, hover types, type diagnostics, file symbol outlines, and project-wide symbol search — name resolution and type inference that tree-sitter and ripgrep cannot do. Use when you need to follow an import to a definition, find all real uses of a symbol (excluding same-named-but-unrelated ones), get an inferred type, surface type errors, outline a file, or search symbols across a project. Triggers on "go to definition", "find references", "what type is", "resolve this symbol", "symbol outline", "find symbol in project", "pyright", "type-check this file".

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。

Source b-roll for a video edit — classify each moment, scope the search, return vetted candidates, place on the word. Use when the user says "find b-roll", "/find-broll", "source clips for this edit", or wants footage/memes/screenshots to lay over a talking-head video.

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。

Suede AI findings-only code review with full context: changed files, callers, contracts, and deploy surface. Covers TypeScript, React, Next.js, database, Swift/iOS, OWASP, accessibility, SEO, observability, commit hygiene, and deploy risk, ranked P0-P3 with file:line evidence and a fix path. Use when asked to review a diff, PR, branch, or commit range, find the bugs before merge, check a change for security or accessibility problems, or judge whether a change is safe to deploy. Emits findings and a ship gate, not a grade. NOT FOR: the A-F letter grade alone (use suede-code-grader); findings plus grade in one pass (use suede-code); making CI enforce the result on every merge (use suede-ci-gate); root-causing a live bug or failing test (a private Suede Labs companion, not in this pack).

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Use whenever the user wants to find, shortlist, vet, or enrich US software development firms — custom software, web development, mobile app development, backend/API development, DevOps/cloud, system integration, and hosting. Triggers on "find a software dev shop in Austin", "shortlist three custom-software firms with healthcare experience", "we need a mobile app developer for our iOS launch", or "pull contact info for these 10 dev shop domains", even when described indirectly (build a tool, ship a feature, technical partner). Drives the ServiceGraph API (api.servicegraph.co) — a 100k+ US firm catalog filterable by industry, services, location, size, ratings. Defer to find-web-developer for strictly website/landing-page projects. Defer AI/ML, ML pipelines, model building, and data-engineering asks — those are a sibling industry, not software development. Skip in-house engineer hires, code-writing/debugging tasks, cloud-product comparisons, hardware/civil engineering, non-US firms, individual freelancers.

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Use whenever the user wants to find, shortlist, vet, or enrich US AI/ML/data consulting firms (consultancies) — AI/ML development, MLOps, generative AI / LLM apps (RAG, chatbots, agents), computer vision, NLP, recommendation systems, data engineering, BI/analytics. Triggers on "find an AI/ML consulting firm to build our recommendation engine", "shortlist three RAG/LLM consultancies for an enterprise chatbot", "compare three AI/ML consulting firms with strong ratings", or "pull contact info for these 8 AI consultancy domains", even when described indirectly (we want to use AI for X, deploy ML to production). Drives the ServiceGraph API (api.servicegraph.co) — a 100k+ US firm catalog filterable by industry, services, location, size, ratings. Defer to find-software-developer for general app/backend work where AI is just a feature. Skip in-house ML/data hires, LLM/AI-tool comparisons (ChatGPT vs Claude), "how do I fine-tune X" DIY questions, AI courses for individuals, non-US firms, individual freelancers.

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Use whenever the user wants to find, shortlist, vet, or enrich US public-relations and communications agencies — media relations, crisis comms, investor relations (IR), product-launch PR, tech/startup PR, healthcare PR, B2B PR, public affairs, brand reputation, and internal communications. Triggers on "find me a tech PR agency in NY", "shortlist three IR firms for our IPO", "we need crisis comms help for a brand reputation issue", or "pull contact info for these 10 PR firm domains", even when described indirectly (we need press, get us into TechCrunch, manage our brand reputation). Drives the ServiceGraph API (api.servicegraph.co) — a 100k+ US firm catalog filterable by industry, services, location, size, ratings. Defer to find-marketing-agency when scope is broader marketing beyond PR/comms. Skip in-house PR/comms hires, "write me a press release" DIY asks, PR-software comparisons (Cision, Muck Rack), influencer-marketplace questions, non-US firms, individual freelance PR people.

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。

The branded entry point to ServiceGraph — use whenever the user explicitly names **ServiceGraph** — "use ServiceGraph to…", "what datasets does ServiceGraph have", "search ServiceGraph for…", "look this up in ServiceGraph", "pull contacts from ServiceGraph for these domains", "how many credits do I have on ServiceGraph". ServiceGraph is a multi-dataset platform of metrics-enriched business data for founders — where to launch, who to email, who to hire. This skill explains how to drive the API (api.servicegraph.co / mcp.servicegraph.co) against ANY dataset — discover what datasets exist, discover a dataset's schema and filters, search free brief rows, and unlock contact + metric detail with credits. Dataset-agnostic by design — it discovers everything through the API and never assumes which datasets or fields exist. When the user describes an intent WITHOUT naming ServiceGraph (e.g. "find a PR agency in NY"), defer to the matching specific skill (find-pr-agency, find-marketing-agency, find-law-firm, …); this skill is for explicit ServiceGraph requests and for datasets no specific skill covers yet. Skip non-US firms, consumer/personal services, and individual freelancers.

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 whenever the user wants to find, shortlist, vet, or enrich US engineering firms — civil, structural, MEP, mechanical, electrical, geotechnical, transportation, environmental, and manufacturing. **For real-world engineering (buildings, infrastructure, manufacturing) — NOT software engineering.** Triggers on "find civil engineering firms in Florida for transportation", "shortlist three structural engineering firms with high-rise experience", "MEP consultancy for a hospital project", or "pull contact info for these 12 engineering firm domains", even when described indirectly (PE-stamped drawings, building-permit review). Drives the ServiceGraph API (api.servicegraph.co) — a 100k+ US firm catalog filterable by industry, services, location, size, ratings. Defer software-dev / "engineering team" / SaaS-architecture asks to find-software-developer. Skip in-house engineering-manager hires, DIY questions, software-product comparisons (Revit, AutoCAD), non-US firms, individual freelancers.

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。

Find actual code issues in a repo that aren't listed in GitHub issues. missing tests, inconsistent patterns, outdated dependencies, documentation gaps. Presents findings to the user for evaluation. Use when you want to make proactive contributions beyond existing issues, or when no good issues are available. Not for browsing the existing issue tracker. Use oss-find-issue for that.

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Finds and compares 184,900 swimming spots worldwide (beaches, lakes, bathing places) with live water temperature, wind, UV and wave signals, local guides and source-backed activity providers, via the public BeachFinder MCP server.

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。

Track validated Codex Security findings in Linear, Jira, GitHub issues, or draft GitHub security advisories. Use it for one finding or an explicitly selected batch of up to 25 findings tracked as Linear, Jira, or GitHub issues. Includes duplicate checks, exact previews, approval-gated writes, and readback. Do not use it for scans or fixes.

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。

Web search with full page content extraction. Use this skill whenever the user asks to search the web, find articles, research a topic, look something up, find recent news, discover sources, or says "search for", "find me", "look up", "what are people saying about", or "find articles about". Returns real search results with optional full-page markdown — not just snippets. Provides capabilities beyond default agent web search tools.

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Chart a too-big effort as a shared map of decision tickets on the Gaia headquarters issue tracker, then resolve them one at a time until the way to the destination is clear. Use when someone says: "this is too big for one session", "chart a map", "wayfinder map", "plan this effort", "what do we need to decide first", "open a wayfinder", "work the map", "what's on the frontier", or /wayfinder. Covers any gaia-research org repo — gaia-skill-tree, gaia-research, gaia-skill-heaven and beyond — but every map and every ticket lives on ONE tracker: gaia-research/gaia-skill-tree. This is cartography (planning an effort as decisions), NOT triage of an existing backlog — for that use /gaia-triage.

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。

Verify code-review or security-review findings for false positives using deep codebase tracing, framework-aware analysis, and web research. Produces a .verified.md report alongside the original. Use when a review report has been generated and needs independent verification, or when user runs /verify-findings, mentions "verify review", "check false positives", or "validate findings".

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。

Curate .unikit/MCP-RECHECK-NOTES.md — the project's log of findings about the configured engine MCP server. Four jobs: re-stamp (the server moved, so every entry is suspect), replay (reproduce a `replay: safe` finding inside a disposable sandbox to see whether it still holds), retire (offer to drop what was fixed or went upstream), and upstream (print a ready diff for the packaged INDEX.md). Use for "audit the MCP notes", "are these findings still true", "recheck the MCP traps", "clean up MCP-RECHECK-NOTES", "the server was updated — revisit the notes". Replaying mutates a live editor, so it starts by telling you how to prepare it — save your scene, open an empty one — and asks once before touching anything. Everything it creates lives under a single UNIKIT_AUDIT_<runid> prefix, is deleted in one action, and the scene is never saved. To record a NEW finding use /unikit-mcp-trap instead.

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。

Findy Campus Hackathon #2「Cloudflareで好きなAIアプリを作って公開！」のキックオフ・伴走スキル。 参加者がAIアプリを作り始めるとき、作れるものの幅（Cloudflareを使うか / AIを使うか / デプロイするか）を 押し付けずに示し、スターターの degit からスキル導入・実装・公開まで、最適な既存スキルを案内して伴走する。 ハッカソンを始める・プロジェクトを立ち上げる・Cloudflareにデプロイする・詰まったとき、に使う。

Retrieve up-to-date library, framework, and project documentation using scripts + MCP tools (Context7, Context Hub) with intelligent fallback. Use this skill whenever the user or agent needs documentation for any library, framework, API, SDK, or internal project spec. Triggers on "docs for [X]", "how does [library] work", "find documentation", "API reference for", "look up [feature] in [library]", "latest docs", "what's the API for", "find our [internal spec]", or any request that requires current, accurate documentation rather than relying on training data. Always prefer this skill over raw WebSearch for documentation retrieval — it returns structured, context-efficient 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。

Post findings from the most recent review output as inline GitHub PR comments and record them in today's daily note. Use when invoked as `$pr-post-review-findings` or when the user asks to post review findings to the current PR.

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。

Web search with full page content extraction. Use this skill whenever the user asks to search the web, find articles, research a topic, look something up, find recent news, discover sources, or says "search for", "find me", "look up", "what are people saying about", or "find articles about". Returns real search results with optional full-page markdown — not just snippets. Provides capabilities beyond Grok's built-in WebSearch.

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。

システムログを分析してエラーの根本原因を特定し、段階的に深堀りしていくデバッグ専門家スキル。 アプリケーションログ、システムログ、クラウドサービスログなど様々な形式に対応。 5 Whys、タイムライン分析、Fishbone分析などのRCA（根本原因分析）手法を用いて 問題の本質を突き止め、再発防止策まで提案する。 Use when analyzing system logs to find error root causes, debugging application issues, or performing technical post-mortem analysis with log data. For organizational incident management processes (post-incident review, corrective action plans, incident reports without log data), use incident-rca-specialist instead. Triggers: "analyze this log", "find the root cause", "debug this error", "why is this failing", "log analysis", "what caused this crash", "troubleshoot this issue"

4人の異なる専門家ペルソナ（20年ベテランエンジニア、TDDエキスパート、Clean Codeエキスパート、バグハンター）で ソースコードを批判的にレビューするスキル。設計判断、テスト容易性、可読性、バグ検出の観点から コードの問題を検出し、改善提案を行う。Python/JavaScriptに対しては追加のチェックポイントを適用。 バグハンターは状態遷移、例外パス、依存関係、非同期競合に特化し、本番環境での問題を事前に検出する。 Use when reviewing source code from multiple expert perspectives to find design flaws, testability issues, code quality problems, and runtime bugs. Triggers: "critical code review", "multi-persona code review", "expert code review", "code quality assessment", "find bugs".

Aktiver Finder/Router für die eigenen lokalen Skills (Analogon zu using-superpowers). IMMER zu Beginn einer nicht-trivialen Aufgabe nutzen, um zu prüfen, ob ein user-Skill passt, und zum richtigen Skill zu routen. Aktiviert sich bei „welcher Skill passt", „gibt es dafür einen Skill", „skill finden", oder generell vor Aufgaben, die ein lokaler Skill besser löst als ad-hoc-Arbeit.

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。

/nix/store 配下の store path・ファイルを特定するときに必ず参照する。`find /nix/store` で名前を総当たりする前に読む。「あのパッケージの store path が知りたい」「nix-unit のバイナリはどこ」「flake input の実体パスを知りたい」「derivation の出力パスを取りたい」「store の中のこのファイルを探したい」「store path が実在するか確かめたい」といった場面が対象。/nix/store は数万エントリあり深さ無制限の find は完了しない（実測: 20秒でも終わらず出力ゼロ）。同梱の collect_store_lookup.sh が入力の種別判定・一意な解決・候補収集・実在確認までを決定論的に行うので、まずそれを実行してから分析する。nix-locate が返す path はローカルに存在しないことがあるという反直感的な挙動も、データとして検出される。