You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
DEFAULT PIPELINE for all tasks requiring execution. You (Claude) are the strategic orchestrator. Codex agents are your implementation army - hyper-focused coding specialists. Trigger on ANY task involving code, file modifications, codebase research, multi-step work, or implementation. This is NOT optional - Codex agents are the default for all execution work. Only skip if the user explicitly asks you to do something yourself.
Use this skill whenever you need to pay for an x402 URL, transfer USDC to an address, inspect OmniClaw balances or ledger entries, or expose a paid API with omniclaw-cli serve. OmniClaw is the Economic Execution and Control Layer for Agentic Systems. The CLI is the zero-trust execution layer: buyers use `omniclaw-cli pay`, sellers use `omniclaw-cli serve`. Use this skill for the CLI execution path only, not for owner setup, policy editing, wallet provisioning, or Financial Policy Engine administration.
Delegates coding tasks to Codex CLI for prototyping, debugging, and code review. Use when needing algorithm implementation, bug analysis, or code quality feedback. Supports multi-turn sessions via SESSION_ID.
Example skill that demonstrates the gitclaw skills system. Use this to test skill loading and script execution.
Use this when the user needs to choose between multiple ML routes after survey but before committing to implementation. Compares candidate approaches, selects one, records rejected routes, and keeps a fallback.
Forces the generation of test_assertions.json during the implementation plan phase. v7.2.0 enhanced with severity gates, dependencies, timeouts, and Claw-as-Validator support.
Record implementation pitfalls, debugging insights, and lessons learned into structured devlog documents. Triggers on completing any implementation task that encountered issues, after debugging sessions, after E2E testing, or when user says "record this", "document this pitfall", "add to devlog", "踩坑记录". MUST be invoked after any implementation phase that involved non-trivial bug fixes or workarounds.
Use in pre-implementation (idea-to-design) stages to understand spec/requirements and create a correct implementation plan before writing actual code. Turns ideas into a fully-formed PRD/design/specification and implementation-plan. Creates design docs and task lists in docs/wip/. --- # Task Analysis Process **Goal: Before writing any code, make sure you understand the requirements and have an implementation plan ready.** ## Ideas and Prototypes _Use this for ideas that are not fully thought out and do not have a fully-formed design/specification and/or implementation-plan._ **For example:** I've got an idea I want to talk through with you before we proceed with the implementation. **Your job:** Help me turn it into a fully formed design, spec, implementation plan, and task list. See [idea-process.md](./idea-process.md). ## Continue WIP Feature _Use this to resume work on a feature that already has design docs and a task list in `/docs/wip/`._ **For example:** Let's continue working on the auth system. **Your job:** Review the current state of the feature, understand what's been done and what's next, then proceed with implementation. See [existing-task-process.md](./existing-task-process.md).
State-machine driven iterative planning and execution for complex coding tasks.
Technical design collaboration through natural dialogue. Adapts to expertise level and problem complexity through understanding, exploration, and validation stages. Use when user asks to brainstorm ideas for new features or systems requiring architectural decisions before implementation begins.
Build apps on Databricks Apps platform. Use when asked to create dashboards, data apps, analytics tools, or visualizations. Invoke BEFORE starting implementation.
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:
