- 📄 SKILL.md
code-review
Review Python code for bugs, security issues, and best practices
Review Python code for bugs, security issues, and best practices
RESTful API design best practices and conventions guide
Debugging guidelines and best practices
Review and analyze a skill against best practices for length, intent scope, and trigger patterns
Perform comprehensive code reviews with best practices, security checks, and constructive feedback. Use when reviewing pull requests, analyzing code quality, checking for security vulnerabilities, or providing code improvement suggestions. --- # Code Review Analysis ## Table of Contents - [Overview](#overview) - [When to Use](#when-to-use) - [Quick Start](#quick-start) - [Reference Guides](#reference-guides) - [Best Practices](#best-practices) ## Overview Systematic code review process covering code quality, security, performance, maintainability, and best practices following industry standards. ## When to Use - Reviewing pull requests and merge requests - Analyzing code quality before merging - Identifying security vulnerabilities - Providing constructive feedback to developers - Ensuring coding standards compliance - Mentoring through code review ## Quick Start
Review ESP32 firmware architecture for RTOS safety, memory management, error handling, and embedded best practices.
Generate AZ-104 practice questions that feel like the real exam without copying it. Every item is grounded in current Microsoft Learn content, uses modern Azure terminology, and follows Microsoft-style exam item rules (scenario-first, plausible distractors, no trick wording). Use when the user asks for practice questions, quiz items, or exam prep.
RESTful API design patterns, versioning, and best practices
This skill should be used to review and audit the bt CLI for adherence to CLI best practices from clig.dev AND internal codebase patterns. It checks source code for help text, flags, error handling, output formatting, subcommand structure, pattern consistency, and more. Triggers on "review my code", "audit the CLI", "check CLI best practices", or /bt-review. --- # CLI Best Practices Review Audit the `bt` CLI codebase against two reference documents: 1. **clig.dev guidelines** — industry CLI best practices 2. **bt codebase patterns** — established internal conventions for consistency ## When to Use - When a user asks to review, audit, or check the CLI - When triggered via `/bt-review` - After implementing new commands or subcommands - Before releases to ensure CLI quality ## Review Process ### 1. Scope the Review
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: