- 📄 SKILL.md
autonomous-bug-fix
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Use token-efficient CLI patterns instead of verbose MCP output when direct shell tools are enough. Provides JSON or compact-output conventions for gh, mgrep, psql, and similar tools.
Add or extend API Platform resources in php-service-template using DDD and CQRS-friendly patterns.
Use whenever a user shares or describes a 104 履歷 (resume) or LinkedIn profile and wants it reviewed, scored, or improved — even if they only paste a fragment or describe it verbally.
Compose an arrangement for a tape — plan which elements enter and exit over time, then generate a playable CCArrangement.
Perform a self-review of a PR before requesting human review. TRIGGER when user invokes /pr-selfcheck or when the git workflow reaches the self-review step after PR creation. Accepts a PR number as an argument.
Use when setting up a project environment — installing dependencies, verifying builds, detecting the tech stack. Covers Phase 0 of a new session.
Set price, IV, or activity-based alerts with contextual notifications. Alert types include IV rank threshold crossing, price support/resistance breaks, unusual activity detection, earnings approaching, and VRP signal changes.
Writes Python code following FiftyOne's official conventions. Use when contributing to FiftyOne, developing plugins, or writing code that integrates with FiftyOne's codebase.
Build multi-step LLM reasoning chains in n8n using Groq, OpenAI, or Claude for structured data extraction, categorization, scoring, and analysis. Use this skill whenever the user wants to chain multiple LLM calls together in an n8n workflow — phrases like "extract entities then categorize", "multi-step LLM prompt", "chain_llm", "LLM pipeline", "classify and score", "entity extraction then enrichment". Also use when processing call transcripts, customer messages, or any unstructured text through multiple analysis passes in n8n. Prefer this pattern over single-shot prompts whenever the output requires both extraction AND reasoning, since single-shot hallucinates categories while chains let each step verify the previous.
Run Hermes Local Memory peer review, reflection, deterministic maintenance, candidate review, card review, and verification through provider tools.
Use when an agent needs the smallest useful eval pack to catch regressions or false confidence early.
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: