- 📄 SKILL.md
code-refactoring-guide
Evaluate code quality and suggest refactoring opportunities before committing. Ensure Cooper's codebase stays clean and maintainable.
Evaluate code quality and suggest refactoring opportunities before committing. Ensure Cooper's codebase stays clean and maintainable.
Bitbucket CLI for Data Center and Cloud. Use when users need to manage repositories, pull requests, branches, issues, webhooks, or pipelines in Bitbucket. Triggers include "bitbucket", "bkt", "pull request", "PR", "repo list", "branch create", "Bitbucket Data Center", "Bitbucket Cloud", "keyring timeout".
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
Nightly pipeline for integrating newly captured external article notes into Brain knowledge surfaces. Use when: 文章整合, article notes integration, nightly article sync, update article relations, topic index update, article knowledge graph, 前一天文章整理, 或 run the 02:00 article pipeline. --- # Article Notes Integration 把前一天新增或待整合的 Article Notes,转成可检索、可关联、可继续提炼的 Brain 知识输入层。 ## Purpose 这个技能负责 **文章 ingestion 之后的 nightly integration**,而不是原始外部文章采集本身。 它处理的是: 1. 扫描昨天新增或尚未 integrated 的 article notes 2. 校验并补足结构 / frontmatter / relation 状态 3. **交叉引用更新**(见下方 Cross-Reference Protocol,每次 ingest 后执行) 4. 更新 topic / domain / project 相关的轻量图谱入口 5. 生成 open questions / pattern candidates / article-derived graph signals 6. 输出高价值 article candidates,供后续 flywheel amplification 使用 ## Primary Inputs - Brain root: `{{BRAIN_ROOT}}` - Source notes: `03-KNOWLEDGE/02-WORKING/01-ARTICLE-NOTES/` - Candidate set: - 前一天新增 article notes - 或 `integration_status != integrated` 的 article notes - Read-only context: - related domain notes - `03-KNOWLEDGE/99-SYSTEM/01-INDEXES/` 下已有 topic / topic-map / open-question surfaces - `05-PROJECTS/` 下 project briefs(若能稳定识别项目) ## Required Outputs
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations.
Use this skill when designing, documenting, or generating REST API specifications using OpenAPI/Swagger. Trigger on keywords like OpenAPI, Swagger, API spec, REST documentation, API schema, request body, response schema, and API client generation. Also apply when adopting design-first API development, validating API contracts, or setting up auto-generated API documentation for FastAPI, Express, or NestJS endpoints. --- # OpenAPI & REST API Design ## When to Use - Documenting REST APIs - Generating API clients - API design-first development - Defining webhook contracts - Establishing pagination, versioning, or auth patterns for a new service ## When NOT to Use - Internal-only scripts or automation that do not expose HTTP endpoints - CLI tools and command-line utilities without a REST interface - GraphQL APIs where a different specification format applies --- ## Core Patterns ### 1. OpenAPI 3.1 Specification Structure A complete spec skeleton showing every top-level section. Use `$ref` to split large specs into per-resource files. ```yaml
用于撰写、补写、压缩、仿写、规范化交付中文毕业论文、毕业设计论文、技术报告和课程设计论文。用户提到论文、样文、学校模板、参考文献、摘要、图表、截图、Word 成稿、查重口吻优化,或需要基于真实项目代码生成论文正文时必须使用。本技能内置样文结构学习、样式提取、章节控字、参考文献筛选、Mermaid/PlantUML 图表处理、Chrome MCP 页面截图工作流,以及 doc/docx Word 成稿交付工作流。
Claim the AI bounty on tDVV by delegating to the canonical repo SKILL and its branch docs; this public skill is AA/CA only and requires explicit write confirmation.
Category-aware design skill that builds distinctive, production-grade UIs. Palettes, font pairings, UX patterns, shadcn/token integration, empty-error-loading copy, secondary slop signals, and a pre-ship second pass. Framework-agnostic.
Build and check Lean 4 proofs. Triggers: "lean build", "check proofs", "run lean", "verify proofs", "lean".
Local command skill example with explicit command whitelisting.
Cognithor - Agent OS: Local-first autonomous agent operating system. 16 LLM providers, 17 channels, 112+ MCP tools, 5-tier memory, A2A protocol, knowledge vault, voice, browser automation, Computer-use, self-healing, self-improving. Python 3.12+, Apache 2.0.
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: