391 件 ・ 関連度順
概要と使いどころ
Searching internet for technical documentation using llms.txt standard, GitHub repositories via Repomix, and parallel exploration. Use when user needs: (1) Latest documentation for libraries/frameworks, (2) Documentation in llms.txt format, (3) GitHub repository analysis, (4) Documentation without direct llms.txt support, (5) Multiple documentation sources in parallel
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。
Synchronize curated Agent Skills across approved repositories with policy checks and verification. Use when publishing or updating managed skills, validating a repository mirror, or selecting a safe sync scope. Triggers on "sync public skills", "publish skills", "public 公開", "skill sync", "repository mirror".
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。
Idiomatic Go - package and interface design, error wrapping, table-driven tests, generics, the modern standard library (slices/maps/cmp/errors.Join), current syntax, and logging discipline. Use when writing, reviewing, or refactoring any Go code, especially code drifting toward Java/Spring shapes (deep layer trees, generic repositories, heavy frameworks) - even if the user never says "idiomatic". Distilled from spf13/go-skills and adapted to this repo.
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 preparing or publishing a local project as a clean GitHub repository. Covers new repositories, private staging releases, public README cleanup, updates to existing remotes, and research-code packaging without datasets, checkpoints, papers, or generated artifacts.
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 and exploit vulnerabilities in the AI Supply Chain by injecting malicious models, datasets, or dependencies. Use this skill to simulate advanced persistent threats (APTs) compromising Hugging Face repositories, manipulating pre-trained weights (Model Poisoning), and exploiting insecure deserialization during model loading (e.g., Pickle files).
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。
Procedure for controlled, human-gated outbound README badge provisioning PRs (Issue #1817). Preflights upstream repositories, ensures single-badge placement with deep links, and records campaign outcomes without automated retries or multi-badge noise.
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。
Generates Spring Boot 3.x configurations, creates REST controllers, implements Spring Security 6 authentication flows, sets up Spring Data JPA repositories, and configures reactive WebFlux endpoints. Use when building Spring Boot 3.x applications, microservices, or reactive Java applications; invoke for Spring Data JPA, Spring Security 6, WebFlux, Spring Cloud integration, Java REST API design, or Microservices Java architecture.
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。
Strategic roadmap management for GitHub repositories. Syncs ROADMAP.md with GitHub Issues and labels, bootstraps roadmap files from scratch, runs brainstorming sessions with boundary checking, and provides quick status summaries. Use when managing project planning, syncing roadmap state, or exploring feature ideas.
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。
Search and work with the user's GitHub repositories through GitHub's official 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。
Use when the user wants Codex to build, refine, test, validate, or list CLI-Anything harnesses for GUI applications or source repositories. Adapts the full CLI-Anything methodology to Codex without changing the generated Python harness format.
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 this skill when creating, scaffolding, reviewing, or maintaining Python Home Assistant custom integrations, including work on custom_components, manifests, config flows, options flows, config entries, platforms/entities, DataUpdateCoordinator, integration automation triggers, diagnostics, repairs, discovery/networking, authentication, HACS-ready repositories, or Home Assistant integration quality scale compliance.
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。
Clean Architecture patterns for Android and Kotlin Multiplatform projects — module structure, dependency rules, UseCases, Repositories, and data layer patterns.
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 starting work in a repository under repositories/ that may lack CI configuration. Detects missing CI workflows (GitHub Actions, GitLab CI, CircleCI) and alerts the user to add one. Skips repos marked as research-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。
Analyze any GitHub repository in AI-friendly format. Convert entire repos to single markdown documents, generate architecture diagrams with Mermaid, inspect structure trees, language breakdowns, and recent activity. Includes GitHub URL tricks, API shortcuts, and advanced search techniques. Read-only analysis — never executes code from repositories. Built for AI agents — Python stdlib only, no dependencies. Use for repository analysis, code architecture review, open source research, GitHub intelligence, repo documentation, and codebase understanding.
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。
Auto-activate for sqlspec, SQLSpec, SQLFileLoader, drivers, query builders, named SQL, filters, pagination, Arrow, framework extensions, ADK stores, or observers. Not for ORM repositories — use advanced-alchemy.
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。
Build production CI/CD pipelines with GitHub Actions. Implements matrix builds, caching, deployments, testing, security scanning. Use for automated testing, deployments, release workflows. Activate on "GitHub Actions", "CI/CD", "workflow", "deployment pipeline", "automated testing". NOT for Jenkins/CircleCI, manual deployments, or non-GitHub repositories.
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。
Given an article DOI or PubMed ID, discover and download the genomics data files deposited by the authors (VCF, FASTA, H5AD, CSV, JSON, BAM, etc.) from public repositories such as GEO, ENA, Zenodo, Figshare, Dryad, and OSF.
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。
Search an index of public repositories, GitHub issues, merged pull requests, repository READMEs, and curated documentation sites. Use when a programming question needs external documentation or upstream 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。
Azure Container Registry SDK for Python. Use for managing container images, artifacts, and repositories.
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。
Discover and analyze trending GitHub repositories from TrendShift and other sources — evaluate usefulness, extract learnings, and identify valuable skills/tools
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 professional visual assets for GitHub repositories — architecture diagrams, social cards, and README banners.
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 production-ready public GitHub repositories with comprehensive documentation, automated setup, and quality assurance
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。
Set up and optimize repositories for AI coding agents. Creates minimal AGENTS.md, CLAUDE.md symlink, docs/REQUIREMENTS.md, docs/BUSINESS-RULES.md, feedback loops, and deterministic enforcement (Claude Code hooks, OpenCode plugins). Use when user wants to make a repo AI-friendly, set up AGENTS.md/CLAUDE.md, document requirements/business rules for AI, add pre-commit hooks for AI workflows, or optimize codebase structure for coding agents.
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。