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Use this skill when the user wants to "report a bug", "file an issue", "report an issue", "submit a bug report", or report any problem with the mcp-apps plugin to the GitHub repository.

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Use this skill when the user wants to "report a bug", "file an issue", "report an issue", "submit a bug report", or report any problem with the canvas-apps plugin to the GitHub repository.

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Draft matter status reports from emails, call notes, and updates. Internal and client-facing formats, RAG logic, variance commentary, escalation flags. Use when asked to draft a status report, write a project update, summarise matter progress, prepare a client report, create a weekly or monthly update, convert emails into a status summary, or produce any kind of matter reporting. Also triggers when the user pastes email threads and asks what the status is, or needs to turn internal updates into client-facing reports.

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Provides comprehensive Turborepo monorepo management guidance for TypeScript/JavaScript projects. Use when creating Turborepo workspaces, configuring turbo.json tasks, setting up Next.js/NestJS apps, managing test pipelines (Vitest/Jest), configuring CI/CD, implementing remote caching, or optimizing build performance in monorepos

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Routes substantive ML, AI, data, scientific-computing, and software-engineering requests to the smallest useful set of managed repository skills. Invoke proactively when a request names or implies a package, framework, model family, dataset, modality, workflow, backend, deployment target, evaluation method, or implementation approach that may benefit from repository guidance, even if no repository is named. Narrow progressively from area to family to repository root: inspect only the one or two most likely area pages; compare candidates by capability, task surface, model/data format, training versus inference versus evaluation intent, runtime constraints, and root-skill description; then open only the selected root and relevant sub-skills, references, or scripts. Select multiple repositories only when each adds a distinct capability. Do not load the whole collection, treat dependencies or incidental integrations as capabilities, choose by name alone, or force a match when no exact taxonomy family applies.

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Automatically generate clear, actionable issue reports from failing tests and repository analysis. Analyze test failures to understand expected vs. actual behavior, identify affected code components, and produce well-structured Markdown reports suitable for GitHub Issues or similar trackers. Use when a test fails, when debugging issues, or when the user asks to create an issue report, generate a bug report, or document a test failure.

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Remove AI-generated patterns from QA reports, bug reports, test summaries, status updates, and quality communications. Detects and rewrites robotic test-result language, template-sounding status updates, inflated severity descriptions, and generic stakeholder reports — without inventing facts. Makes QA writing sound like a real engineer wrote it. Use when: "humanize report," "rewrite QA summary," "fix test report," "make this sound human," "clean up status update." Not for: general prose, blog, or marketing-copy cleanup — use the global humanizer skill. Not for: classifying or routing CI failures — use ai-bug-triage. Related: ai-bug-triage, qa-metrics, qa-dashboard, quality-postmortem.

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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".

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Generate comprehensive status reports for git repositories. Analyzes commits, codebase structure, type errors, branch health, dependency status, GitHub PRs/issues/CI, working tree changes, and optionally integrates with `td` (task management CLI) if a `.todos` folder is present. **TRIGGERS - Use this skill when:** - User asks for the status of a git project or repo - User asks "what's going on in [project]" or "give me an overview of [repo]" - User wants a project summary, progress report, or codebase overview - User asks about recent commits, code structure, or project health - User says "check my project" or "project status" **Output:** A rich, structured text report covering overview, branches, commit history, codebase breakdown, GitHub activity, dependency health, issues/errors, working tree changes, task management, and summary.

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🇺🇸 Your dev team ships features nobody asked for while user-reported bugs pile up for months. Operations blames engineering for ignoring users; engineering blames operations for not understanding technical constraints. This gives you the complete Product × Engineering × Operations alignment SOP — from unified backlog to 10-day sprint cadence to veto power rules. What's inside: • Dual-layer Kanban system (master backlog + sprint board with unified tagging) • 10-day sprint standard process (Day 1 dev → Day 6 testable build → Day 10 ship) • Issue template with reproducibility requirements (3x reported = auto-severe) • Tri-party alignment meetings (daily standup / sprint planning / sprint review) • Operations veto power on releases (P0 bug = block shipping) • User feedback → product iteration closed loop (beta testing + interview SOP) • Core metrics framework (acquisition → activation → retention → monetization → referral) • Technical debt management (20-30% sprint capacity reserved) • Ready-to-use templates: Bug Report, Sprint Planning, Responsibility Matrix Built from: Real product strategy meetings + beta testing frameworks. References Supabase sprint model, Manus/DeepSeek commercialization alignment. By @WeiYipei. 🇨🇳 你的研发团队在做没人要的新功能，用户反馈的 Bug 堆了三个月没人动。运营觉得研发不听用户，研发觉得运营不懂技术。这份 SOP 给你从统一看板到 10 天迭代节奏到一票否决权的完整产研运协同框架。 🇯🇵 開発チームは誰も求めていない機能を作り、ユーザーから報告されたバグは何ヶ月も放置。このSOPは、統一バックログから10日スプリント、リリース拒否権まで、プロダクト×エンジニアリング×オペレーションの完全な連携フレームワークを提供します。 🇰🇷 개발팀은 아무도 요청하지 않은 기능을 만들고, 사용자가 보고한 버그는 몇 달째 방치됩니다. 이 SOP는 통합 백로그부터 10일 스프린트, 릴리스 거부권까지 제품×개발×운영 완전 협업 프레임워크를 제공합니다. Triggers: "product ops" | "engineering operations" | "product development SOP" | "sprint planning" | "iteration management" | "cross-functional alignment" | "product engineering ops" | "dev ops collaboration" | "产研运协同" | "迭代管理" | "产品研发运营" | "プロダクト開発運営" | "제품개발운영"

确认漏洞后产出正式 SRC/0day 提交稿 DOCX 报告的收口 skill。仅在漏洞已确认、准备成稿时使用——负责查重、过分层验证门、按固定 DOCX 骨架生成报告（Heading 2 章节 + Step 式 PoC + 内嵌真实截图）、语义化命名、放对目录、处理驳回追加。不负责挖掘/验证漏洞本身。TRIGGER：用户说"写报告/出报告/成稿/提交稿/生成漏洞报告"，或漏洞已验证到位准备交付时；或 /report。EN: Turns confirmed vulnerabilities into submission-ready DOCX reports for SRC/0day platforms (verification gates, fixed layout, step-style PoC, mandatory real screenshots). Trigger on "write report" or /report.

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Act as a project-management copilot (PM/PMO) for the delivery loop: charters, plans and schedules, estimates, risk registers, status reports, scope changes, stakeholder communication, meeting actions, lessons learned, and portfolio roll-ups, in a per-project `_project/` workspace. Use whenever the user wants to start, plan, track, rescue, or report on a project: "kick off this project", "make a project plan / timeline / WBS", "what date can I commit to", "build a risk register", "run a pre-mortem", "write the weekly status report", "the deadline slipped, what now", "turn this meeting into action items", "review my project portfolio", in any language ("quản lý dự án", "gestion de projet", "プロジェクト管理", "项目管理"), even when they never say "project management". Also use whenever a `_project/` directory exists and the user asks about schedule, deadline, risk, status, scope, budget, or stakeholders. Not for what to build (product-manager) or company-level bets (strategy-board).

Build a reporting pipeline — scheduled reports with SQL queries, delivery via Slack or email, threshold alerts, and historical comparison. Use when asked for "automated reports", "scheduled report", "email digest", or "Slack alerts for metrics".

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Audits Claude Code repositories. Two-phase workflow — Phase 1 sweeps 14 hygiene categories (permissions, hooks, CLAUDE.md bloat, Skills hygiene, process-abstraction, plus structural) and an optional 7-layer leak check. Phase 2 executes [APPROVED] markers from the report file. Use for repo cleanup, pre-distribution sanity, post-feature hygiene, environment audit, process-abstraction discovery. Trigger on "audit my CC repo," "sweep my repository for hygiene," "check this CC environment," "find process abstraction candidates," "review my CLAUDE.md," "clean up my .claude directory," "pre-distribution hygiene check," "find layer leaks in my CC setup." Routes structural findings to rootnode-cc-design REMEDIATE. Composes with rootnode-critic-gate. CC-only — does not scan Claude Projects. Do NOT use for building a Skill (use rootnode-skill-builder), compiling a prompt (use rootnode-prompt-compilation), scoring a single prompt (use rootnode-prompt-validation), or auditing a Project (use rootnode-project-audit).

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Create parameterized Quarto or R Markdown reports that can be rendered with different inputs to generate multiple variations. Covers parameter definitions, programmatic rendering, and batch generation. Use when generating the same report for different departments, regions, or time periods; creating client-specific reports from a single template; building dashboards that filter to specific subsets; or automating recurring reports with varying inputs.

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Create consistent nn_cfd W&B experiment comparison reports from selected run IDs using wandb and wandb_workspaces. Use this whenever the user asks to report experiment results, create a W&B Report, compare CFD training/eval runs, document baseline-vs-variant outcomes, reproduce the project experiment report template, or publish a leaderboard-style report for milieu/nn_cfd.

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PDF Trade Report Generator — scans for all TRADE-*.md analysis files, extracts scores/signals/levels, and generates a professional multi-page PDF investment report (ReportLab). Triggered by "trade report-pdf".

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Scaffold a new Tip in the ai-product-dev-tips repository following the existing directory/format conventions, and register its link in the root README.md. Use this whenever the user wants to add, create, or write a new Tip in this repo — e.g. "nlp_processing に〜の Tip を追加して", "新しい Tips を作って", "〜の解説 Tip を書いて", "this repo に〜のネタを追加". It picks the right category and next sequential number, matches the README format of nearby Tips, generates code scaffolding (Dockerfile / requirements.txt / *_cpu.sh / *_gpu.sh / *.py) only when the Tip needs runnable code, and inserts the link into the correct <details> section of the root README. Trigger this even if the user doesn't say the word "skill" — any request to add a new entry to this Tips collection should use it.

Update an EXISTING Tip in the ai-product-dev-tips repository — edit its README, add or fix code, refresh outdated information, fix mistakes — while keeping the repo's format conventions and syncing the root README link. Use this whenever the user wants to update, edit, fix, revise, refresh, correct, or complete an existing Tip in this repo — e.g. "nlp_processing/29 の README を更新して", "〇〇の Tip を最新仕様に直して", "image_processing/11 の説明を修正して", "あの Tip のリンク切れを直して", "この Tip を完成版にして". It locates the target Tip, studies the current format conventions (shared with the ai-product-dev-tips-create skill), applies consistent edits, verifies the content with web research (no fabrication), and syncs the root README link (title text / [In-progress]). This is for UPDATING existing Tips, not creating new ones — to add a brand-new Tip use the ai-product-dev-tips-create skill instead. Trigger this even if the user doesn't say "skill".

Review the UI and style files changed in the working tree against this repo's own design system, before they are saved or committed. Runs the same deterministic check as the CLI's --check flag (no tokens, about a second): hardcoded colours where a token exists, near-identical colour twins, off-scale spacing, radii, font sizes and shadows, typefaces outside the system, arbitrary Tailwind values, static inline styles, !important, duplicate component definitions and imports of the copy to avoid, new tokens that copy an existing one, chart colours written by hand where the repo keeps a chart palette (and one calm warning asking for a palette where it keeps none), on a repo built on MUI, Mantine, Chakra or Ant Design, colours or pixel sizes written onto kit components where the theme has a value, and on a Tailwind theme or a shadcn repo, palette classes such as text-gray-500 where the theme names a colour of that kind. Findings name the file, the line and the fix. This is the small, fast check for what just changed; the roast skill is the full scan of the whole repo with a report.

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Prevent common AI report pitfalls — bug blending, inflated threat models, and generic language. Train Claude with your best past reports for concise, technical submissions. Based on Critical Thinking Bug Bounty Podcast Episode 166.

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Write a structured weekly or bi-weekly program status report for stakeholders. Use when the user says "write a status report", "program update", "stakeholder update", "weekly status", "RAG status", "program health report", "what do I send to leadership", "write the update for [program]", or needs to communicate delivery progress - even if they don't explicitly say "status report". Produces a concise, scannable report with RAG status, blockers, and decisions needed.

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Read and search GitHub repository documentation via gitmcp.io MCP service. **WHEN TO USE:** - User provides a GitHub URL - User mentions a specific repo in owner/repo format - User asks "what does this repo do?", "read the docs for X repo", or similar - User wants to search code or docs within a repo

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Analyze Amazon product, sales, Amazon Ads, retail-readiness, and Best Seller Rank data to find commercially actionable growth opportunities. Use when Codex needs to identify which ASINs, campaigns, keywords, search terms, product targets, placements, categories, or BSR movements deserve more investment, optimization, harvesting, bid/budget changes, retail-readiness fixes, investigation, protection, or controlled scaling across Sponsored Products, Sponsored Brands, Sponsored Display, search term reports, targeting reports, campaign reports, placement reports, advertised/purchased product reports, Business Reports, organic performance, and BSR history.

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。