Explore an Obsidian vault using Enzyme — surface connections between ideas, find latent patterns across notes. Use when the user wants to explore their thinking, draw connections, or search their vault by concept rather than keyword.
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Assess your codebase's resistance to AI-assisted development tools.
Analyze code and LLM practices against Claude Code's production-grade engineering patterns. Use when the user asks to 'assess my code against Claude Code', 'how would Claude Code do this', 'what patterns does CC use for X', 'review my LLM approach', or invokes /what-would-cc-do:assess or /what-would-cc-do:claudecodefy.
Refactor bloated AGENTS.md, CLAUDE.md, or similar agent instruction files to follow progressive disclosure principles. Splits monolithic files into organized, linked documentation.
Multi-agent orchestration framework for Claude Code. Automatically delegates tasks to cheaper, faster sub-agents (Haiku 4.5, Sonnet 4.6) while maintaining Opus-level quality through verification. Use when working on any coding task — Hydra activates automatically to route file exploration, test running, documentation, code writing, debugging, security scanning, and git operations to the optimal agent. Saves ~50% on API costs. --- # 🐉 Hydra — Multi-Headed Speculative Execution > *"Cut off one head, two more shall take its place."* > Except here — every head is doing your work faster and cheaper. ## ⛔ MANDATORY PROTOCOLS — NEVER SKIP These protocols are NON-NEGOTIABLE. Skipping them is a framework violation. ### Protocol 1: Sentinel Scan After Code Changes When ANY agent returns output containing `⚠️ HYDRA_SENTINEL_REQUIRED`, you MUST — before doing ANYTHING else, before presenting results to the user, before running any other agents — dispatch hydra-sentinel-scan with the files and changes listed in the trigger block. **This is blocking.** The user does NOT see the code changes until sentinel completes. If you present code changes to the user without running sentinel first, you have violated the framework's core safety guarantee.
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,
Qdrant provides client SDKs for various programming languages, allowing easy integration with Qdrant deployments.
Complete guide for AI agents to understand, install, and operate ZhiYing
Use when you need to deduplicate concurrent or repeated async calls, prevent duplicate API requests, cache async function results, add automatic retry with exponential backoff, memoize heavy computation wrapped in Promise, replace SWR/Provider for request sharing, invalidate cache with flush, or persist cached data to localStorage, sessionStorage, node-fs, or redis. Covers install, usage, and plugin code generation for idmp in browser, React, and Node.js projects.
Builds and edits Simulink, System Composer, Stateflow, and Simscape models. Use when modifying model structure, parameters, ports, connections, or Stateflow chart internals.
Build multi-step LLM reasoning chains in n8n using Groq, OpenAI, or Claude for structured data extraction, categorization, scoring, and analysis. Use this skill whenever the user wants to chain multiple LLM calls together in an n8n workflow — phrases like "extract entities then categorize", "multi-step LLM prompt", "chain_llm", "LLM pipeline", "classify and score", "entity extraction then enrichment". Also use when processing call transcripts, customer messages, or any unstructured text through multiple analysis passes in n8n. Prefer this pattern over single-shot prompts whenever the output requires both extraction AND reasoning, since single-shot hallucinates categories while chains let each step verify the previous.
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:
