RESTful API design conventions including endpoint naming, HTTP methods, status codes, pagination, error handling, and versioning patterns. Use when designing APIs, creating endpoints, or reviewing API contracts.
Send HTTP API requests using curl. Use when the user asks to call an API, fetch data from a URL, send POST/PUT/PATCH/DELETE requests, work with REST or GraphQL endpoints, upload files, authenticate with Bearer tokens or API keys, debug HTTP responses, or interact with any web service via HTTP.
API design patterns for REST, gRPC, and GraphQL. Use for: api design, REST, gRPC, GraphQL, protobuf, schema design, api versioning, pagination, rate limiting, error format, OpenAPI, API authentication, JWT, OAuth2, API gateway, webhook, idempotency.
AI SDK plugin patterns - tool configuration, schema validation, API integration. Uses @youdotcom-oss/api utilities.
Use when managing AI Hub account, API keys, balance, usage, or API endpoints. Use when user says "AI Hub", "add AI credits", "create API key", "check AI usage", "auto-recharge", "AI Hub endpoint", "AI Hub base URL", "how to use AI Hub API", "LLM API", "AI API", "OpenAI compatible", "Anthropic API", "GPT", "Claude", "Gemini", "DeepSeek", or "Grok" in the context of Zeabur.
This skill should be used when the user asks to "analyze this framework's API", "outside-in outline for X", "API-first learning plan", "create a learning outline for X", "trace the public API", "analyze the API surface", "api-blueprint", or any request to map a Java framework's API surface for outside-in reimplementation. Analyzes a Java framework's source code and produces an API-first learning outline (api-outline.md) that maps the public API surface, traces each capability inward through implementation layers, generates ASCII call-chain diagrams, and creates a buildable project skeleton. --- # API Blueprint — API-First Learning Outline ## Philosophy: Outside-In, API-First The fastest way to learn a framework and confidently contribute to it is to start where the **user** starts — the public API. Instead of hunting for the framework's internal "heart" and building outward (v1 approach), this skill: 1. **Identifies the API surface** — the classes, interfaces, and methods that framework users actually import and call in their application code 2. **Organizes features as vertical slices** — each feature represents one API capability, traced from the public method all the way down through internal layers 3. **Orders by usage tier** — most commonly used APIs first, power-user/advanced APIs last
当验证API实现、检查REST约定、分析API设计或调试API问题时使用。验证API结构、设计和最佳实践。
AI-powered API documentation generation tool that auto-generates comprehensive API docs from source code, including OpenAPI/Swagger specs, Postman collections, and markdown documentation with examples and authentication details.
Develop applications using the Docyrus API with @docyrus/api-client and @docyrus/signin libraries. Use when building apps that authenticate with Docyrus OAuth2 (PKCE, iframe, client credentials, device code), make REST API calls to Docyrus data source endpoints, construct query payloads with filters, aggregations, formulas, pivots, and child queries, or integrate with external connectors (discover connectors, send requests through provider auth, run actions). Triggers on tasks involving Docyrus API integration, @docyrus/api-client usage, @docyrus/signin authentication, data source query building, Docyrus REST endpoint consumption, connector discovery, or external provider requests.
Build production-ready REST APIs with versioning, documentation, and rate limiting. Use when the user wants to create API endpoints, build a REST API, add API resources, or generate OpenAPI documentation. Triggers: "build api", "create endpoint", "api resource", "rest api", "api documentation", "swagger", "json api", "graphql".
REST API design conventions, error shapes, versioning, and pagination patterns. Use when designing or reviewing any HTTP API.
在 MergeMeet 專案中建立或修改 API 路由時使用此 skill。它強制執行「禁止尾隨斜線」標準以防止 404 錯誤。適用於處理 FastAPI 路由、修復 404 錯誤或審查 API 端點定義時。
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:
