Interact with GitHub using the gh CLI restricted to REST API only (no GraphQL). Use when the user wants to work with GitHub issues, pull requests, repos, releases, or Actions — especially in sandboxed environments where the GraphQL endpoint may be blocked. Trigger keywords - github, gh, pull request, PR, github issue, github actions, workflow, release, gh api.
Transform messy prompts into well-structured, effective prompts — single, multi-agent, or reverse-engineered from great outputs.
Ask any question about Claude Code features — setup, best practices, automation, models, plugins, MCP, configuration, and more. Reads relevant reference docs to give accurate, detailed answers.
PrediHermes, also named geopolitical-market-sim, tracks geopolitical topics, selects relevant open Polymarket contracts near deadline, generates MiroFish seed packets from WorldOSINT data, runs or inspects MiroFish simulations, and resolves historical branches or injected actors from local artifacts. Use this when the user wants PrediHermes, recurring geopolitical prediction-market monitoring, topic tracking, counterfactual actor injection, simulation comparison, or a local automation path from news + markets into MiroFish.
ClawMem agent reference — detailed operational guidance for the on-device hybrid memory system. Use when: setting up collections/indexing/embedding, troubleshooting retrieval, tuning query optimization (4 levers), understanding pipeline behavior, managing memory lifecycle (pin/snooze/forget), building graphs, or any ClawMem operation beyond basic tool routing.
Design system expertise — component creation, token management, Figma workflow.
Projitive is an MCP-first governance skill for agent-driven delivery. Use this before changing task states or writing governance artifacts. Core flow: taskNext -> taskContext -> execute -> verify -> taskNext. Always prefer Projitive MCP methods for discovery, context, and proactive task advancement.
Onbard yourself to this repo that might have X number of other agents running on it. Whenever you are starting off or asked to onboard to team use this skill to give yourself extra awareness of multi-agent and worker context, as well as goals and identity.
>-
INVOKE THIS SKILL at the START of any LangChain/LangGraph/Deep Agents project, before writing any agent code. Determines which framework layer is right for the task: LangChain, LangGraph, Deep Agents, or a combination. Must be consulted before other agent skills.
>-
Use Cerul's video search API from Codex or Claude-style agents. Trigger when a user wants to search videos with Cerul, inspect Cerul usage, or integrate Cerul search into scripts or agent workflows. Requires CERUL_API_KEY and optionally CERUL_BASE_URL.
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:
