ProductionOS instinct-based learning system. Observes sessions via hooks, extracts patterns, creates atomic instincts with confidence scoring, and auto-promotes high-confidence patterns across projects.
Inspect local shell scripts for unsafe patterns and summarize findings for a reviewer.
Use when working with gh CLI. Provides patterns for PRs, issues, reviews, and repository operations.
Use this skill when the user asks to create a new pattern, add a layout, or make a reusable slide template. Triggers on: 'add pattern', 'create pattern', 'new layout', 'パターン作って', 'レイアウト追加'.
Automatically discover novel, statistically validated patterns in tabular data. Find insights you'd otherwise miss, far faster and cheaper than doing it yourself (or prompting an agent to do it). Disco systematically searches for feature interactions, subgroup effects, and conditional relationships you wouldn't think to look for, validates each on hold-out data with FDR-corrected p-values, and checks every finding against academic literature for novelty. Returns structured patterns with conditions, effect sizes, citations, and novelty scores.
Modern tidyverse patterns, style guide, and migration guidance for R development. Use this skill when writing R code, reviewing tidyverse code, updating legacy R code to modern patterns, or enforcing consistent style. Covers native pipe usage, join_by() syntax, .by grouping, pick/across/reframe operations, filter_out/when_any/when_all, recode_values/replace_values/replace_when, tidy selection, stringr patterns, naming conventions, and migration from base R or older tidyverse APIs. Use the R (btw) MCP tools to resolve function documentation and library references automatically.
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
Comprehensive project architecture blueprint generator that analyzes codebases to create detailed architectural documentation. Automatically detects technology stacks and architectural patterns, generates visual diagrams, documents implementation patterns, and provides extensible blueprints for maintaining architectural consistency and guiding new development.
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:
