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概要と使いどころ
Manage `@metaharness/darwin` bench suites — `bench create {repo}` scaffolds a JSON suite from a repo's test corpus; `bench verify {suite.json}` checks suite well-formedness. Bench suites are the fixed evaluation corpora that `harness-evolve --bench {suite.json}` scores variants against, decoupling evolution from the repo's natural tests. Degrades gracefully when @metaharness/darwin is absent.
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。
7-section repo readiness report from `metaharness genome {path}`. Returns repo_type / agent_topology / risk_score / mcp_surface / test_confidence / publish_readiness. Pure-read; degrades gracefully (ADR-150).
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。
Create a high-signal bug issue or PR in the repo that owns the defect. Use this whenever the user asks to report, file, open, or triage a LazyCodex, lazycodex-ai, omo-codex, Codex plugin, or upstream Codex CLI bug, especially when they need source-backed root cause, reproduction steps, fix guidance, and GitHub routing.
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。
Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos).
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 security vulnerabilities in a codebase or repository with Strix — a white-box AI security review that reads your source, reasons about the actual data flow and authorization model, then exploits what it finds in a live sandbox so every reported issue has a working proof-of-concept instead of a noisy static-analysis alert. Covers injection, XSS, SSRF, broken access control and IDOR, insecure deserialization, secrets in code, unsafe dependencies, and business-logic flaws. Use when the user asks to security-scan, security-review, or audit their code, repo, or pull request for vulnerabilities.
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。
Builds evidence-traceable market research reports and assumption-driven market sizing or forecast scenarios. Use for market definition, industry and customer evidence, competitive landscapes, TAM/SAM/SOM reconciliation, forecast sensitivity, and auditable report scaffolds.
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 the user needs to run GitNexus CLI commands like analyze/index a repo, check status, clean the index, generate a wiki, or list indexed repos. Examples: "Index this repo", "Reanalyze the codebase", "Generate a wiki"
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。
Cherry-pick commits from chatbox-pro repo to the open chatbox repo, handling mobile-only files, package name differences, and other repo-specific exclusions.
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。
Power BI report visualization design prompt for creating effective, user-friendly, and accessible reports with optimal chart selection and layout design.
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。
Adopt repository-level harness engineering for coding agents. Use when a user wants to prevent repeated AI coding-agent mistakes by turning failures into durable instructions, drift checks, regression tests, failure memory, and adoption reports tailored to the target repository.
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。
Create, update, and manage GitHub issues using MCP tools. Use this skill when users want to create bug reports, feature requests, or task issues, update existing issues, add labels/assignees/milestones, manage repository labels, set issue fields (dates, priority, custom fields), set issue types, manage issue workflows, link issues, add dependencies, or track blocked-by/blocking relationships. Triggers on requests like "create an issue", "file a bug", "request a feature", "update issue X", "set the priority", "set the start date", "create a label", "rename a label", "list repo labels", "link issues", "add dependency", "blocked by", "blocking", or any GitHub issue management task.
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。
Creates structured bug reports for defects found during Oracle-to-PostgreSQL migration. Use when documenting behavioral differences between Oracle and PostgreSQL as actionable bug reports with severity, root cause, and remediation steps.
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。
Pre-breach impact analysis: inventories sensitive data (PII, PHI, PCI-DSS, credentials), traces data flows, scores exposure vectors, and produces a regulatory blast radius report with fine ranges sourced verbatim from GDPR Art. 83, CCPA § 1798.155(a), and HIPAA 45 CFR § 160.404. Cost benchmarks from IBM Cost of a Data Breach Report (annually updated). All citations in references/SOURCES.md for verification. Use when asked: "assess breach impact", "what data could be exposed", "calculate blast radius", "data exposure analysis", "how bad would a breach be", "quantify data risk", "sensitive data inventory", "data flow security audit", "pre-breach assessment", "worst-case breach scenario", "breach readiness", "data risk report", "/data-breach-blast-radius". For any stack handling user data, health records, or financial information. Output labels law-sourced figures (exact) vs heuristic estimates (planning only). Does not replace legal counsel.
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。
Copilot left 14 review comments on your PR — half are nits. Hours of fix → reply → resolve → re-request, and each round lands MORE comments. This skill runs loop engineering: auto-triggers Copilot Code Review via GraphQL (no @copilot mention), triages every open thread (Copilot, humans, advanced-security) with a fix / decline / escalate rubric, dispatches parallel fix sub-agents that obey the repo build/test/lint conventions, commits per iteration, replies+resolves citing the pushed SHA, then re-triggers until HEAD is reviewed with zero threads awaiting the agent's reply (remaining open threads are explicit hand-offs to the human — escalated declines, design tradeoffs). You merge a clean PR; the bot runs it. Trigger phrases: "address copilot comments", "run a copilot review loop", "fix this PR", "iterate on copilot feedback". Repo-agnostic, gh CLI + PowerShell. Full autopilot needs repo Triage/Write; external PR authors get single-iteration mode plus manual re-trigger (UI 🔄 or substantive-commit push).
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。
Make any repo AI-ready — analyzes your codebase and generates AGENTS.md, copilot-instructions.md, CI workflows, issue templates, and more. Mines your PR review patterns and creates files customized to your stack. USE THIS SKILL when the user asks to "make this repo ai-ready", "set up AI config", or "prepare this repo for AI contributions".
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 local Q&A session JSONL files and produce a complete, auditable English Markdown weekly report over consecutive time windows, with all data required for downstream Feishu document and whiteboard rendering. Use for requests such as "analyze the latest week of sessions," "generate a community Q&A weekly report," or "compare with last week." This skill does not ingest other message sources or create/upload online documents.
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。
Create institutional-quality equity research initiation reports through a 5-task workflow. Tasks must be executed individually with verified prerequisites - (1) company research, (2) financial modeling, (3) valuation analysis, (4) chart generation, (5) final report assembly. Each task produces specific deliverables (markdown docs, Excel models, charts, or DOCX reports). Tasks 3-5 have dependencies on earlier tasks.
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。
Uses the Linux Audit framework (auditd) with ausearch and aureport utilities to detect intrusion attempts, unauthorized access, privilege escalation, and suspicious system activity. Covers audit rule configuration, log querying, timeline reconstruction, and integration with SIEM platforms. Activates for requests involving auditd analysis, Linux audit log investigation, ausearch queries, aureport summaries, or host-based intrusion detection on Linux.
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 the scheduled repo-hygiene workflow runs from GitHub Actions (or an operator dry-run) to scan the repository for small, certain docs/test/code hygiene issues and fix them as one batched branch.
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。
Generate test report. Use when user says "test report", "results summary", "test status", "show results", "test dashboard", or "how did tests go".
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 and synthesizing product/user research as a method-and-repository discipline — selecting the right method for the goal (generative interviews vs usability test vs concept test vs validation), computing method-based saturation/sample size with an explicit confidence level, or synthesizing coded observations into insights while flagging single-source anecdotes. Never fabricates user insight; an insight requires recurrence across independent participants. Distinct from product-team/ux-researcher-designer (persona/journey artifacts), product-discovery (discovery-sprint planning), and experiment-designer (live A/B) — this is the research-ops method + insight-repository layer.
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 the user says 'build me an app', 'create a project from this spec', 'scaffold a new repo', 'generate a starter', 'turn this idea into code', 'bootstrap a project', 'I have requirements and need a codebase', or provides a natural-language project specification and expects a complete, runnable repository. Stack-agnostic: Next.js, FastAPI, Rails, Go, Rust, Flutter, and more.
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。
Senior Project Manager for enterprise software, SaaS, and digital transformation projects. Specializes in portfolio management, quantitative risk analysis, resource optimization, stakeholder alignment, and executive reporting. Uses advanced methodologies including EMV analysis, Monte Carlo simulation, WSJF prioritization, and multi-dimensional health scoring. Use when a user needs help with project plans, project status reports, risk assessments, resource allocation, project roadmaps, milestone tracking, team capacity planning, portfolio health reviews, program management, or executive-level project reporting — especially for enterprise-scale initiatives with multiple workstreams, complex dependencies, or multi-million dollar budgets.
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。
Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos).
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。