Генерирует полную .claude/ структуру автоматизации для любого проекта — агенты, пайплайны, скиллы, memory, hooks, settings. Автоопределение режима fresh/validate/resume.
Sharpens, refines, and optimizes AI agent skills through real usage — learns from mistakes, reviews quality, and improves over time. Observes skill execution in the current conversation, analyzes up to four sources (conversation friction, file diffs, user feedback, static diagnostic), and proposes concrete improvements to the target skill's SKILL.md. Works with Claude Code and compatible SKILL.md-based agent frameworks. Use after executing any skill: `/skill-sharpen [name]` or `/skill-sharpen` to auto-detect. `--review` processes accumulated lessons.
Audit the Claude Code CHANGELOG.md for plugin-relevant changes. Builds FLOW's integration surface model, fetches new changelog entries, categorizes as Adopt/Remove/Adapt, and files issues for approved items.
Capture a worker's execution JSONL into claude-code-viewer's auto-debug project for inspection
Adversarial AI code/plan review. Codex reviews, Claude fixes, iterative loop until approved. Auto-detects plan/code/code-vs-plan mode.
Improve or create AGENTS.md files that serve as shared instructions for AI coding agents (Claude, Gemini, etc.). Use this skill whenever the user mentions AGENTS.md, CLAUDE.md, GEMINI.md, agent instructions, agent configuration, or wants to improve how AI agents behave in their project. Also trigger when the user says "improve my instructions", "agents file", "update my rules", or asks about best practices for configuring coding agents. If in doubt and the task involves AI agent instruction files, use this skill. --- You help users write and improve AGENTS.md files — shared instruction files that AI coding agents (Claude, Gemini, etc.) read at the start of every session. The goal is a single file that works across platforms via symlinks. Read `references/BEST_PRACTICES.md` before analyzing or writing any AGENTS.md content. It contains the patterns extracted from official documentation that inform every decision below. ## Core Workflow ### 1. Assess the Current State Before proposing changes, read the target file and evaluate it against these dimensions: - **Length** — is it under 200 lines? Ideally under 100? Agents have a budget of ~150 instructions they can reliably follow, and the system prompt already uses ~50. - **Structure** — does it use markdown headers to group related instructions? Or is it a wall of text / a single giant list? - **Specificity** — are instructions concrete and verifiable ("use 2-space indentation") or vague ("write clean code")? - **Contradictions** — do any rules conflict with each other? - **Scope mixing** — does it blend personal preferences with project-level standards? - **Signal-to-noise** — does every instruction pass the conciseness test ("would removing this cause the agent to make mistakes")? Are there instructions the agent would follow anyway without being told? - **Completeness** — is it missing key sections (Priorities, Never/Hard Rules, Common Commands, Architecture, Workflow, Tooling)? Score: 1 = all present, 2 = 1-2 missin
../../../skills/claude-code/SKILL.md
This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", "disallowedTools", "block tools", "agent denylist", "maxTurns", "agent memory", "mcpServers in agent", "agent hooks", "background agent", "resume agent", "agent teams", "permission rules", "permission mode", "delegate mode", "agent team", "team lead", "teammate", "multi-agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.
Guide for creating custom Claude Code subagents. Use when user wants to create a new agent (or update an existing agent) that handles specific types of tasks with custom prompts, tool restrictions, and permissions. Triggers on requests to create agents, subagents, custom agents, or when user wants specialized AI assistants for specific workflows.
Project-specific build process for the Builder workflow. Builds frontend assets for claudecode_webui.
Core methodology for AI-powered scientific hypothesis generation. Auto-loaded when discovering connections, generating hypotheses, exploring cross-disciplinary links. Includes facet recombination, adversarial prompting, evolutionary refinement, groundedness checking, and hypothesis card format.
A skill for automating AI CLI tool interactions by handling common prompts and managing continuous operation.
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:
