- 📄 SKILL.md
plan
Plan mode — inspect context, write a markdown plan into the active workspace's `.echo-agent/plans/` directory, and do not execute the work.
Plan mode — inspect context, write a markdown plan into the active workspace's `.echo-agent/plans/` directory, and do not execute the work.
Inspect external prediction model implementations and adapt them to EasyTSF task contracts. Use when the user provides model code, class definitions, forward logic, or config fragments and wants Codex to classify the target task as `sequence_prediction`, `graph_prediction`, or `grid_prediction`, determine the current repository fit, and produce either a direct adaptation plan or a repository extension plan.
receptron/mulmoclaude の `plans/` 直下にあるマージ済み plan を `plans/done/` にアーカイブし、コード/docs 内の全 stale 参照を `plans/done/<name>.md` に書き換えて PR を作成する。`plans` 整理、`plans の done を移動` 等で起動。PR #265 / PR #817 と同形式の sweep。
Pre-implementation red-team analysis. Use when a plan is high-risk, critical path, or expensive to reverse. Challenges plans before code is written — finds edge cases, security holes, scalability bottlenecks, error propagation risks, and integration conflicts. Catches flaws at plan time (10x cheaper than post-implementation).
This skill should be used when the user asks to "set up OpenClaw", "get started", "onboard me", "plan my setup", or "help me choose channels". Conducts an interactive interview, then generates a tailored deployment plan.
Trigger immediately when the user says any of: 'design this', 'plan the implementation', 'plan this out', 'how should we build', 'implementation plan', 'before I write code', 'design the feature', 'figure out how to build'. Also use for implementation design once desired behavior is known: before creating features, building components, adding functionality, or modifying behavior. Do not skip this skill and start coding directly — if a trigger phrase appears, route here even if auto mode is active. Do not use for open-ended product brainstorming or vague requirements; use spec first. No code until design is approved.
Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".
Restructure and review engineering documents with source-fidelity-first rules. Preserve original meaning and useful source form, avoid adding new facts or forced decisions, and keep issue/risk-first feedback. Use for design docs, refactor plans, migration plans, PR narratives, and runbooks.
Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".
Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".
Use inside the plan plugin when the user wants to execute an existing implementation plan, continue from the authoritative Linear issue plan, or resume work after leaving Plan mode. Consumes the routed Linear issue identity plus the canonical linked-document `tracked-plan/1`, requires valid tracked-plan and plan-event helpers before execution, updates only tracked-plan runtime state, and appends validated progress events instead of inferring authority from chat.
Converts a Lousy Agents spec or master plan into a structured Beads (bd) dependency graph of epics and tasks. Use when asked to 'convert plan to issues', 'create beads from spec', 'populate beads', 'plan to graph', or 'break down spec into tasks'.
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: