Use when modifying the Codex SPECTRE install flow, SessionStart continuity, project skill syncing, registry injection, or Codex-specific runtime files.
Apply frontend UI aesthetics judgment for web interface generation, review, and refactor tasks. Use when working on hierarchy, composition, responsiveness, accessibility, or visual polish in frontend code.
Automatically analyze a codebase and generate an architecture diagram with zero configuration. Use when the user asks to "diagram this repo", "visualize the architecture", "auto diagram", or requests a codebase overview without specifying components. Do NOT use when the user provides a specific description, sample diagram, or component list — use the excalidraw skill instead.
This skill should be used when the user asks to "create a Temporal workflow", "write a Temporal activity", "debug stuck workflow", "fix non-determinism error", "Temporal Python", "Temporal TypeScript", "Temporal Go", "Temporal Golang", "workflow replay", "activity timeout", "signal workflow", "query workflow", "worker not starting", "activity keeps retrying", "Temporal heartbeat", "continue-as-new", "child workflow", "saga pattern", "workflow versioning", "durable execution", "reliable distributed systems", or mentions Temporal SDK development.
Write Yo async code and algebraic effect handlers. Use this when working with IO, Future, JoinHandle, using/given, io.async, io.await, io.spawn, return, and escape.
Testing-first Open-FDD lab skill: external bench validation, frontend/API parity, BRICK+BACnet verification, overnight triage, and issue filing for confirmed product defects.
Guidelines and best practices for building modern, state-of-the-art web applications using the htag v2 framework.
Answer a question about a GRACE project using full project context. Use when the user has a question about the codebase, architecture, modules, or implementation — loads all GRACE artifacts, navigates the knowledge graph, and provides a grounded answer with citations.
REST 및 GraphQL API 설계 원칙 가이드. 새로운 API 설계, API 스펙 리뷰, API 설계 표준 수립 시 활용. 트리거: "API 설계", "REST", "GraphQL", "엔드포인트 설계", "API versioning", "API 패턴" 안티-트리거: "프론트엔드 UI", "데이터베이스 스키마만", "CSS/스타일링", "배포/인프라"
GitHub repository access in containerized environments using REST API and credential detection. Use when git clone fails, or when accessing private repos/writing files via API.
Create a well-formed git commit from current changes using session history for rationale and summary; use when asked to commit, prepare a commit message, or finalize staged work. --- # Commit ## Goals - Produce a commit that reflects the actual code changes and the session context. - Follow common git conventions (type prefix, short subject, wrapped body). - Include both summary and rationale in the body. ## Inputs - Codex session history for intent and rationale. - `git status`, `git diff`, and `git diff --staged` for actual changes. - Repo-specific commit conventions if documented. ## Steps 1. Read session history to identify scope, intent, and rationale. 2. Inspect the working tree and staged changes (`git status`, `git diff`, `git diff --staged`). 3. Stage intended changes, including new files (`git add -A`) after confirming scope. 4. Sanity-check newly added files; if anything looks random or likely ignored (build artifacts, logs, temp files), flag it to the user before committing. 5. If staging is incomplete or includes unrelated files, fix the index or ask for confirmation. 6. Choose a conventional type and optional scope that match the change (e.g., `feat(scope): ...`, `fix(scope): ...`, `refactor(scope): ...`). 7. Write a subject line in imperative mood, <= 72 characters, no trailing period. 8. Write a body that includes: - Summary of key changes (what changed). - Rationale and trade-offs (why it changed). - Tests or validation run (or explicit note if not run). 9. Append a `Co-authored-by` trailer for Codex using `Codex <[email protected]>` unless the user explicitly requests a different identity. 10. Wrap body lines at 72 characters. 11. Create the commit message with a here-doc or temp file and use `git commit -F <file>` so newlines are literal (avoid `-m` with `\n`). 12. Commit only when the message matches the staged changes: if the staged diff includes unrelated files or the message describes work that isn't staged, fix the index or revise the message
Adversarial research analysis framework that uses structured Bull/Bear/Arbiter debates to help users make better research judgments. Maintains a belief graph as backend engine, applies statistical calibration discipline, tracks phase transitions, and detects biases.
skill-sample/ ├─ SKILL.md ⭐ Required: skill entry doc (purpose / usage / examples / deps) ├─ manifest.sample.json ⭐ Recommended: machine-readable metadata (index / validation / autofill) ├─ LICENSE.sample ⭐ Recommended: license & scope (open source / restriction / commercial) ├─ scripts/ │ └─ example-run.py ✅ Runnable example script for quick verification ├─ assets/ │ ├─ example-formatting-guide.md 🧩 Output conventions: layout / structure / style │ └─ example-template.tex 🧩 Templates: quickly generate standardized output └─ references/ 🧩 Knowledge base: methods / guides / best practices ├─ example-ref-structure.md 🧩 Structure reference ├─ example-ref-analysis.md 🧩 Analysis reference └─ example-ref-visuals.md 🧩 Visual reference
More Agent Skills specs Anthropic docs: https://agentskills.io/home
├─ ⭐ Required: YAML Frontmatter (must be at top) │ ├─ ⭐ name : unique skill name, follow naming convention │ └─ ⭐ description : include trigger keywords for matching │ ├─ ✅ Optional: Frontmatter extension fields │ ├─ ✅ license : license identifier │ ├─ ✅ compatibility : runtime constraints when needed │ ├─ ✅ metadata : key-value fields (author/version/source_url...) │ └─ 🧩 allowed-tools : tool whitelist (experimental) │ └─ ✅ Recommended: Markdown body (progressive disclosure) ├─ ✅ Overview / Purpose ├─ ✅ When to use ├─ ✅ Step-by-step ├─ ✅ Inputs / Outputs ├─ ✅ Examples ├─ 🧩 Files & References ├─ 🧩 Edge cases ├─ 🧩 Troubleshooting └─ 🧩 Safety notes
Skill files are scattered across GitHub and communities, difficult to search, and hard to evaluate. SkillWink organizes open-source skills into a searchable, filterable library you can directly download and use.
We provide keyword search, version updates, multi-metric ranking (downloads / likes / comments / updates), and open SKILL.md standards. You can also discuss usage and improvements on skill detail pages.
Quick Start:
Import/download skills (.zip/.skill), then place locally:
~/.claude/skills/ (Claude Code)
~/.codex/skills/ (Codex CLI)
One SKILL.md can be reused across tools.
Everything you need to know: what skills are, how they work, how to find/import them, and how to contribute.
A skill is a reusable capability package, usually including SKILL.md (purpose/IO/how-to) and optional scripts/templates/examples.
Think of it as a plugin playbook + resource bundle for AI assistants/toolchains.
Skills use progressive disclosure: load brief metadata first, load full docs only when needed, then execute by guidance.
This keeps agents lightweight while preserving enough context for complex tasks.
Use these three together:
Note: file size for all methods should be within 10MB.
Typical paths (may vary by local setup):
One SKILL.md can usually be reused across tools.
Yes. Most skills are standardized docs + assets, so they can be reused where format is supported.
Example: retrieval + writing + automation scripts as one workflow.
Some skills come from public GitHub repositories and some are uploaded by SkillWink creators. Always review code before installing and own your security decisions.
Most common reasons:
We try to avoid that. Use ranking + comments to surface better skills:
