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Found 523 Skills
Audit and maintain README standards across *-skills repositories with a two-pass workflow (audit first, optional bounded fixes second). Use when running Codex App or CLI automations for skills-repo documentation consistency, profile-aware section schemas, command integrity checks, and discoverability baseline enforcement.
Spawn claude, codex, or gemini CLI workers in tmux panes for parallel task execution
Sync skills (symlinks) and MCP settings from Claude to Gemini CLI and Codex CLI
23 production-ready engineering skills covering architecture, frontend, backend, fullstack, QA, DevOps, security, AI/ML, data engineering, computer vision, and specialized tools like Playwright Pro, Stripe integration, AWS, and MS365. 30+ Python automation tools (all stdlib-only). Works with Claude Code, Codex CLI, and OpenClaw.
6 production-ready project management skills for Atlassian users: senior PM with portfolio management, scrum master with velocity forecasting, Jira expert with JQL mastery, Confluence expert, Atlassian admin, and template creator. MCP integration for live Jira/Confluence automation. Works with Claude Code, Codex CLI, and OpenClaw.
スキルを作成・更新・プロンプト改善するためのメタスキル。 **collaborative**モードでユーザーと対話しながら共創し、 抽象的なアイデアから具体的な実装まで柔軟に対応する。 **orchestrate**モードでタスクの実行エンジン（Claude Code / Codex / 連携）を選択。 Anchors: • Continuous Delivery (Jez Humble) / 適用: 自動化パイプライン / 目的: 決定論的実行 • The Lean Startup (Eric Ries) / 適用: Build-Measure-Learn / 目的: 反復改善 • Domain-Driven Design (Eric Evans) / 適用: 戦略的設計・ユビキタス言語・Bounded Context / 目的: ドメイン構造の明確化 • Clean Architecture (Robert C. Martin) / 適用: 依存関係ルール・層分離設計 / 目的: 変更に強い高精度スキル • Design Thinking (IDEO) / 適用: ユーザー中心設計 / 目的: 共感と共創 Trigger: 新規スキルの作成、既存スキルの更新、プロンプト改善を行う場合に使用。 スキル作成, スキル更新, プロンプト改善, skill creation, skill update, improve prompt, Codexに任せて, assign codex, Codexで実行, GPTに依頼, 実行モード選択, どのAIを使う, IPC Bridge統一, API統一パターン, safeInvoke/safeOn, Preload API標準化, IPC handler registration, Preload API integration, contextBridge, Electron IPC pattern
Universal Cross-session Memory Protocol (Universal Memory Protocol). Enable all AI programming tools to share the same memory system. Applicable to Claude Code / Cursor / Aider / Cline / Codex / Trae / OpenCode. Capabilities: Intelligent Classification / FSRS Decay / Monthly Compression / Multi-layer Retrieval. Triggers: User says "remember"; asks "previous"; sensitive information detected; session ends.
End-to-end remediation workflow for PR review feedback by PR number. Use when Codex must export CodeRabbit issues for a PR, fix every issue completely, commit all fixes in a single commit, and resolve GitHub review threads afterward.
Generate migration deliverables for bringing relevant Megatron changes into MindSpeed after branch alignment and impact mapping are complete. Use when Codex already has a confirmed MindSpeed-to-Megatron branch pairing and needs to produce a migration report, candidate patch, or guarded workspace edits instead of redoing upstream analysis from scratch.
Run a spec-driven agent loop where coding tasks live as markdown specs that move through inbox → active → archive, get implemented by Claude Code or Codex, and pass a review gate before they count as done. Use when the user mentions "loop factory", a "spec-driven loop", an "agent factory", wants repeatable/reviewable agent work, or when a repo has a factory/specs/inbox or factory/specs/active directory. Also covers installing and scaffolding the loop-factory CLI into a project.
Render JSON artifacts into readable UI with an inspect-first, facts-first workflow. Use when Codex needs to turn JSON files, JSON-producing shell commands, CLI output artifacts, or unknown structured payloads into a declarative UI spec that can be rendered natively by the harness or through a terminal-native reference renderer, including cases with repeated child records encoded as aligned arrays.
Professional prompt engineering, context engineering, and AI agent orchestration for coding agents (Claude Code, Codex, Cursor, Gemini CLI). Use when designing CLAUDE.md/AGENTS.md files, writing skills, planning multi-agent pipelines, optimizing token usage, managing session handoffs, or structuring any prompt for maximum agent performance. Do NOT use for general coding tasks or code review.