Create Claude Code agents (autonomous workers with isolated context and restricted tools). Use when the user wants to create an agent, autonomous worker, isolated task runner, or custom subagent. NOT for skills - agents have tool restrictions and run in isolation.
Autonomous multi-batch development agent for long unattended runs. Takes a plan, breaks it into sprint-sized batches, implements with testing and PR-based review, and documents everything for compaction recovery. Use when user says "run overnight", "I'm going offline", "implement this plan", "keep going without me", "do not stop", "I'll be back in the morning", "run this end-to-end", or any indication of autonomous execution. Also use when bootstrapping a new project for overnight runs — the skill generates survival guides and execution logs from templates.
Shared infrastructure for the autonomous dev team skills. Provides workflow enforcement hooks (block-push-to-main, block-commit-outside-worktree, check-design-canvas, etc.) and agent-callable utility scripts (mark-issue-checkbox, reply-to-comments, resolve-threads, gh-as-user). This skill is loaded automatically as background context by other autonomous-* skills. Do not invoke directly.
Autonomous iterative experimentation loop for any programming task. Guides the user through defining goals, measurable metrics, and scope constraints, then runs an autonomous loop of code changes, testing, measuring, and keeping/discarding results. Inspired by Karpathy''s autoresearch. USE FOR: autonomous improvement, iterative optimization, experiment loop, auto research, performance tuning, automated experimentation, hill climbing, try things automatically, optimize code, run experiments, autonomous coding loop. DO NOT USE FOR: one-shot tasks, simple bug fixes, code review, or tasks without a measurable metric.
End-to-end autonomous execution: /define → auto-approve → /do in a single command. Infers task from conversation context when no arguments provided. Add --tend-pr to continue through PR review lifecycle. Use when you want to define and execute a task without manual intervention during planning. Triggers: auto, autonomous define and do, end-to-end, just build it.
Autonomous experiment loop — iteratively improve any measurable metric by modifying code, evaluating results, and keeping improvements. Use when the user says "autoresearch", "start experiments", "optimize this", "run the loop", or wants autonomous iteration on any measurable goal. Reads autoresearch.toml for config. Run `autoresearch init` first. --- ## Autoresearch — Autonomous Experiment Loop You are an autonomous research agent. Your mission: iteratively improve a measurable metric by modifying code, running experiments, and keeping what works. You will run hundreds of experiments. Most will fail. That's expected. The wins compound. --- ### Phase 1: Pre-Flight Before touching any code, validate the environment: ```bash autoresearch doctor ```
Autonomous agentic loop that decomposes any user query into tasks, writes tests first, implements with fresh sub-agents, self-debugs on failure, and learns over time. Use when the user says "super ralph", "ralph this", "break this down and build it", or wants autonomous multi-task execution with quality enforcement.
Start, stop, or manage Clade autonomous coding loops remotely
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:
