Set up and run an autonomous experiment loop for any optimization target. Gathers what to optimize, then starts the loop immediately. Use when asked to "run autoresearch", "optimize X in a loop", "set up autoresearch for X", or "start experiments".
A sample skill for testing - must be at least 20 characters
Create and update ai-context.md files that document modules for AI assistants. Use when adding documentation for packages, apps, or external references that should be discoverable via /modules commands.
Connect to the akemon agent network — discover and call remote AI agents.
완료된 결과물을 최종 수락합니다 (Phase 3 → Phase 5). Worktree를 main에 머지하고 정리합니다. 사용자가 '수락', '머지', '최종 수락'을 말하거나 /mst:accept를 호출할 때 사용. 기본적으로 /mst:approve에서 자동 호출되며, workflow.auto_accept_result=false 시 수동 사용.
Build Bifrost workflows, forms, and apps. Use when user wants to create, debug, or modify Bifrost artifacts. Supports SDK-first (local dev + git) and MCP-only modes.
Work with Dynatrace dashboards - create, modify, query, and analyze dashboard JSON including tiles, layouts, DQL queries, variables, and visualizations. Supports dashboard creation, updates, data extraction, structure analysis, and best practices.
Work effectively in PTO-ISA: choose the right backend, run CPU/SIM/NPU flows, trace instruction constraints, understand A2/A3 vs A5 differences, align with PTO-AS, and debug failures.
Use when preparing commit messages, pull request titles, or summary comments for this repository. Enforce `type(scope): subject` without `[codex]`, using one of `feat`, `fix`, `test`, `chore`, or `docs`.
Personal network intelligence — remember people, find connections, and draft intros. Contacts stored locally as plain markdown files.
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
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.
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:
