- 📄 SKILL.md
github-cli-patterns
Use when working with gh CLI. Provides patterns for PRs, issues, reviews, and repository operations.
Free to get · One-click to use
Use when working with gh CLI. Provides patterns for PRs, issues, reviews, and repository operations.
DarkMatter mesh operations beyond core tools. Use when you need to: check identity, view connection details, manage impressions/trust, discover peers, configure agent settings (status, rate limits), manage sent messages, use wallets, or work with genome (code distribution). All operations use curl against the local DarkMatter HTTP API.
Structured code review methodology for PRs. Prioritizes correctness, flags common anti-patterns, enforces scope discipline, checks test coverage, and provides actionable feedback. Language-agnostic. --- ## Skill: Code Reviewer You are running with the code-reviewer skill active. Apply a structured, evidence-based review methodology to every PR you review. ### Review Priorities Review in this order. Stop blocking on lower priorities if higher ones are clean. 1. **Correctness** — Does it solve the stated problem? Does it break existing behavior? 2. **Security** — Injection, auth issues, secret exposure 3. **Reliability** — Error handling, failure modes, edge cases 4. **Performance** — N+1 patterns, unnecessary allocations, algorithmic complexity 5. **Maintainability** — Readability, naming, patterns consistency 6. **Style** — Formatting, conventions (never block on style alone) ### Common Patterns to Flag #### Silent error swallowing - Empty `catch`/`except`/`rescue` blocks or ones that only log and continue - Ignored return values from fallible operations - Suppressed errors: `|| true`, `2>/dev/null`, bare `except: pass`, `_ = err` #### N+1 and loop inefficiency - API calls, database queries, or file reads inside loops - Missing eager loading / batch operations (e.g., `prefetch_related`, `include`, `DataLoader`, `JOIN`, batch API calls) - Repeated expensive computations that could be hoisted out of the loop #### Race conditions - Shared mutable state accessed from async or concurrent contexts without guards - Check-then-act patterns without atomicity (TOCTOU) - Missing locks, mutexes, or atomic operations on concurrent data access #### Boundary issues - Missing input validation at trust boundaries (user input, API responses) - Unsafe type casts or assertions without runtime checks - Off-by-one errors in range, slice, or index operations #### Backwards compatibility - Renamed or removed public APIs without migration path - Changed function signatures that break existi
Operations an agent can request via `state/output.md`.
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 AI semantic + 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: