Delegate coding tasks to external coding agents (Claude Code, Codex, Pi, OpenCode) via shell. Use when: (1) building new features or apps in a separate project, (2) reviewing PRs, (3) refactoring large codebases, (4) iterative coding that needs file exploration. NOT for: simple one-liner fixes (just edit directly), reading code (use read/file tools), or work inside the SwarmClaw workspace itself.
Manage persistent coding sessions across Claude Code, Codex, Gemini, and Cursor engines. Use when orchestrating multi-engine coding agents, starting/sending/stopping sessions, running multi-agent council collaborations, cross-session messaging, ultraplan deep planning, ultrareview parallel code review, or switching models/tools at runtime. Triggers on "start a session", "send to session", "run council", "ultraplan", "ultrareview", "switch model", "multi-agent", "coding session", "session inbox", "cursor agent".
面向 GPT-5.4 等强模型的轻量 spec-driven / checkpoint-driven coding skill。用于高输入、高频、多轮的代码与 agentic coding 任务，默认短输出、中文沟通、模型自行分解任务；常驻只保留最小 spec、先复述理解、执行前 checkpoint、批准后执行、执行后回写五类关键约束。
Track AI coding tool token usage, costs, and environmental impact
Handles ambiguous or high-impact coding work where missing artifacts, protected-surface changes, or unresolved implementation branches could materially change the implementation. Use for coding tasks that need artifact recovery, guarded clarification, or post-patch verification. Skip trivial, formatting-only, or already explicit single-path work.
Loads coding rules from Qodo most relevant to the current coding task by generating a semantic search query from the assignment. Use when Qodo is configured and the user asks to write, edit, refactor, or review code, or when starting implementation planning. Skip if rules are already loaded.
Persistent spec management for AI coding workflows. Use this skill when the user explicitly mentions specs, forging, or structured planning: says "forge", "forge a spec", "write a spec for X", "create a spec", "plan X as a spec", "resume", "what was I working on", "spec list/status/pause/switch/activate", "implement the spec", "implement phase N", "implement all phases", "generate openapi", or exits plan mode (offer to save as a spec). Also trigger when a `.specs/` directory exists at session start. Do NOT trigger on general feature requests, coding tasks, or questions that don't mention specs or forging — those are normal coding tasks, not spec management. --- # Spec Mint Core Turn ephemeral plans into structured, persistent specs built through deep research and iterative interviews. Specs have phases, tasks, acceptance criteria, a registry, resume context, a decision log, and a deviations log. They live in `.specs/` at the project root and work with any AI coding tool that can read markdown. Whether `.specs/` is committed is repository policy. Respect `.gitignore` and the user's preference for tracked vs local-only spec state. ## Critical Invariants 1. **Single-file policy**: Keep this workflow in one `SKILL.md` file. 2. **Canonical paths**: - Registry: `.specs/registry.md` - Per-spec files: `.specs/<id>/SPEC.md`, `.specs/<id>/research-*.md`, `.specs/<id>/interview-*.md` 3. **Authority rule**: `SPEC.md` frontmatter is authoritative. Registry is a denormalized index for quick lookup. 4. **Active-spec rule**: Target exactly one active spec at a time. 5. **Parser policy**: Use best-effort parsing with clear warnings and repair guidance instead of hard failure on malformed rows. 6. **Progress tracking is sacred**: After completing any task, immediately update SPEC.md (checkbox, `← current` marker, phase marker) AND registry.md (progress count, date). Then re-read both files to verify the edits landed correctly. Never move to the next task without updating both files.
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:
