Refactor high-complexity React components in Dify frontend. Use when `pnpm analyze-component...
npx skills add liqiongyu/lenny_skills_plus --skill "lenny-skillpack-creator"
Install specific skill from multi-skill repository
# Description
Converts a Refound/Lenny Skill into a high-density, agent-executable Skill Pack (Agent Skills standard). Output must be in English.
# SKILL.md
name: "lenny-skillpack-creator"
description: "Converts a Refound/Lenny Skill into a high-density, agent-executable Skill Pack (Agent Skills standard). Output must be in English."
Lenny Skillpack Creator
Your job is to refactor “insight-heavy” Refound/Lenny skills into agent-executable skill packs: boundary-clear, artifact-driven, and testable.
This skill is designed to be compatible with both:
- OpenAI Codex (Codex CLI / IDE skills)
- Claude Code (Agent Skills)
You are NOT writing a blog post. You are producing an installable folder with SKILL.md + references/ (+ optional scripts/).
Language requirement: The generated skill pack (SKILL.md and all referenced templates/checklists) must be written in English.
What you produce
For a given source skill, output an installable skill directory:
<skill-slug>/SKILL.md(short, executable, high-signal)<skill-slug>/references/(templates, checklists, rubrics, question bank, examples, source notes)<skill-slug>/scripts/(optional: lint, scaffolding, batch tools)<skill-slug>/README.md(install + invoke + examples)
Follow the spec in references/SKILL_PACK_SPEC.md.
Inputs you need
Ask for the minimum information needed to proceed. If missing, proceed with explicit assumptions.
Required:
1) The source skill content (SKILL.md or copied text from the Refound page)
2) The intended user / agent context (e.g., “PM agent”, “Hiring assistant”, “Founder operator”, etc.)
3) The intended outputs (what artifacts should exist at the end)
Optional but helpful:
- Tool constraints (read-only? allowed to write files? allowed to run shell?)
- House style / terminology (company-specific sections, metric names, etc.)
Core principle: Convert insights into an execution contract
Every generated SKILL.md must include:
- When to use / When NOT to use
- Input contract (minimum inputs + missing-info strategy)
- Output contract (explicit deliverables)
- Workflow (5–9 steps; each step: inputs → actions → outputs → checks)
- Quality gate (checklist/rubric + “risks / open questions / next steps”)
- Examples (2 positive + 1 boundary/negative)
Use references/TRANSFORMATION_RULES.md as the canonical conversion playbook.
Progressive disclosure (keep SKILL.md short)
Keep SKILL.md operational. Move long content into references/ and cite the files.
Heuristic:
- SKILL.md: 1–2 pages
- references/: everything else (templates, deep notes, long checklists)
Safety + reliability rules
- Default to least privilege. Only request tools you need.
- Never ask for credentials or secrets.
- If the skill writes/modifies code or makes irreversible changes, require explicit confirmation and add rollback guidance.
Use references/SECURITY_GUIDE.md.
Packaging
If the environment supports file operations, create the folder structure and write files.
Otherwise, output a complete file tree in-chat (one file at a time), clearly labeled.
Optional helper scripts (in this skill folder):
- scripts/init_skillpack.py to generate a skeleton
- scripts/lint_skillpack.py to validate structure
- scripts/package_skillpack.py to zip a skill pack
- scripts/fetch_refound_skills.py to download Refound SKILL.md sources from a URL list/manifest
# Supported AI Coding Agents
This skill is compatible with the SKILL.md standard and works with all major AI coding agents:
Learn more about the SKILL.md standard and how to use these skills with your preferred AI coding agent.