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Reference patterns for augmented coding with AI. Use when discussing AI coding patterns, anti-patterns, obstacles, context management, steering AI, or looking up Lexler's patterns collection.
Common analysis patterns for PolicyEngine research repositories (CRFB, newsletters, dashboards, impact studies). For population-level estimates (cost, poverty, distributional impacts), use the policyengine-microsimulation skill instead. --- # PolicyEngine analysis Patterns for creating policy impact analyses, dashboards, and research using PolicyEngine. **For population-level estimates** (budgetary cost, poverty impact, distributional analysis), use the **policyengine-microsimulation** skill instead. This skill covers analysis repo patterns, visualization, and household-level calculations. See `MICROSIMULATION_REFORM_GUIDE.md` for UK-specific microsimulation patterns. ## For Users ### What are Analysis Repositories?
Hybrid adaptive system: Cheatsheet (positive patterns) + Immune (negative patterns). Cheatsheet injects winning strategies before generation. Immune scans output for errors and learns new threats. Both use Hot/Cold tiered memory with multi-domain support. Persistent memory shared with Chimera.
Use when working with gh CLI. Provides patterns for PRs, issues, reviews, and repository operations.
Deep contextual grep for codebases. Expert at finding patterns, architectures, implementations, and answering "Where is X?", "Which file has Y?", and "Find code that does Z" questions. Use when exploring unfamiliar codebases, finding specific implementations, understanding code organization, discovering patterns across multiple files, or locating functionality in a project. Supports three thoroughness levels quick, medium, very thorough.
Learn YOUR false positives from rejections. Run to analyze rejection patterns and integrate with /evaluate-job. Use when reviewing rejections or after "anti-signals", "rejection patterns".
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
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:
