Todo and task management via Eddo MCP server. Use for tracking work items, remembering tasks, managing project todos and time tracking. Supports GTD workflow with contexts and actionability tags (next actions, projects, waiting, someday). Use this skill whenever you need to remember something, track progress, or manage your own task list.
Master REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers. Use when designing new APIs, reviewing API specifications, or establishing... Українською: проектуй API, спроектувати ендпоінт, API дизайн, REST, GraphQL, версіонування API, контракт API, документація API, масштабованість, ресурси, маршрути, HTTP методи, відповідь сервера, структура запиту.
This skill should be used when the user mentions Unraid, asks to check server health, monitor array or disk status, list or restart Docker containers, start or stop VMs, read system logs, check parity status, view notifications, manage API keys, configure rclone remotes, check UPS or power status, get live CPU or memory data, force stop a VM, check disk temperatures, or perform any operation on an Unraid NAS server. Also use when the user needs to set up or configure Unraid MCP credentials.
Build durable, fault-tolerant workflows using Azure Durable Functions with .NET isolated worker and Durable Task Scheduler backend. Use when creating serverless orchestrations, activities, entities, or implementing patterns like function chaining, fan-out/fan-in, async HTTP APIs, human interaction, monitoring, or stateful aggregators. Applies to Azure Functions apps requiring durable execution, state persistence, or distributed coordination with built-in HTTP management APIs and Azure integration.
Clerk backend REST API
HTTP endpoints, SSE streaming, MCP tool servers, and API design patterns for Hybrid. Use when designing new endpoints, streaming responses, or integrating with the agent protocol.
Guides architectural decisions for Deep Agents applications. Use when deciding between Deep Agents vs alternatives, choosing backend strategies, designing subagent systems, or selecting middleware approaches.
Unity API の探索と実行。u api schema で検索、u api call で任意の public static メソッドを呼ぶ。
Use this skill when interacting with MCP servers via CLI. Prefer mcpx over direct MCP SDK/protocol calls for tool discovery, schema inspection, invocation, and Unix-style output composition.
Async HTTP server and client for Python with WebSocket support, middleware, streaming, and server-sent events
Monitor and query Claude Code sessions — list sessions, search conversations, check costs, view AI fluency score, see live running agents. Use when the user asks about their Claude Code usage, costs, session history, or running agents. --- ## You operate the `claude-view` HTTP API **If the claude-view MCP tools are available in your environment, prefer using them instead of curl.** This skill is the fallback for environments without MCP support. claude-view runs a local server on port 47892 (or `$CLAUDE_VIEW_PORT`). All endpoints return JSON (camelCase field names). Base URL: `http://localhost:47892` ## Resolving the server 1. Check if running: `curl -sf http://localhost:47892/api/health` 2. If not running, tell user: `npx claude-view` ## Endpoints | Intent | Method | Endpoint | Key Params | |--------|--------|----------|------------| | List sessions | GET | `/api/sessions` | `?limit`, `?q`, `?filter`, `?sort`, `?offset`, `?branches`, `?models`, `?time_after`, `?time_before` | | Get session detail | GET | `/api/sessions/{id}` | — | | Search sessions | GET | `/api/search` | `?q` (required), `?limit`, `?offset`, `?scope` | | Dashboard stats | GET | `/api/stats/dashboard` | `?project`, `?branch`, `?from`, `?to` | | AI Fluency Score | GET | `/api/score` | — | | Token stats | GET | `/api/stats/tokens` | — | | Live sessions | GET | `/api/live/sessions` | — | | Live summary | GET | `/api/live/summary` | — | | Server health | GET | `/api/health` | — | ## Reading responses All responses are JSON with camelCase field names. Key shapes: **Sessions list:** `{ sessions: [{ id, project, displayName, gitBranch, durationSeconds, totalInputTokens, totalOutputTokens, primaryModel, messageCount, turnCount, commitCount, modifiedAt }], total, hasMore }` **Session detail:** All session fields plus `commits: [{ hash, message, timestamp, branch }]` and `derivedMetrics: { tokensPerPrompt, reeditRate, toolDensity, editVelocity }` **Search:** `{ query, totalSessions, totalMatches, elapsedMs,
Use this skill when developing Node.js backend services or CloudBase cloud functions (Express/Koa/NestJS, serverless, backend APIs) that need AI capabilities. Features text generation (generateText), streaming (streamText), AND image generation (generateImage) via @cloudbase/node-sdk ≥3.16.0. Built-in models include Hunyuan (hunyuan-2.0-instruct-20251111 recommended), DeepSeek (deepseek-v3.2 recommended), and hunyuan-image for images. This is the ONLY SDK that supports image generation. NOT for browser/Web apps (use ai-model-web) or WeChat Mini Program (use ai-model-wechat).
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:
