MIT License

项目介绍

cuzfrog/lissom-skills 是一个托管在 GitHub 上的开源项目,主要使用 Python 编写,采用 MIT License 许可证,目前获得 53 个 Star、6 次 Fork。

仓库全名
cuzfrog/lissom-skills
开源许可证
MIT License
Star 数
53
Fork 数
6

README 摘要

Lissom Skills English · 简体中文 · 日本語 This is repo is deprecated in favor of jie. Why? What's the difference from GSD, SuperPower? Zero Dependency — just plain files. Thin Skill Dispatchers — relentless context protection. Idempotency — hussle-free resume with minimal state. Hammered Specs — no surprise dev experience. /gsd-autonomous /lissom-auto (Context after a 10m task on a small local model with Qwen Code) When to…

完整内容见 GitHub 原始 README 或本页 。

常见问题

lissom-skills 用什么语言开发?

主要使用 Python 编写,采用 MIT License 许可证,目前有 53 个 Star。

lissom-skills 可以免费商用吗?

仓库采用 MIT License 许可证,可免费使用与修改,商业使用请遵守许可证条款(例如保留版权声明与许可声明)。

如何获取 lissom-skills 的源码?

可以直接克隆仓库:git clone https://github.com/cuzfrog/lissom-skills.git,默认分支为 main;安装与运行步骤见仓库 README。

lissom-skills 最近还在维护吗?

仓库最近一次更新为 8月24日,当前没有未关闭的 Issue;Star 数为 53,可作为社区活跃度的参考。

关于

Light weight Claude Skills and Agents for every day tasks.

描述取自 GitHub 官方 API,中文内容由 GitRead 中文社区 编辑团队整理。

语言占比

JavaScript
Python
Shell

贡献者

README

Lissom Skills

License: MIT GitHub stars GitHub last commit GitHub repo size CI

English · 简体中文 · 日本語

┌─┐
│L│░ LISSOM  —  Simple, reliable Claude Code skills & agents
└─┘  SKILLS     for daily dev automation and context protection.

This is repo is deprecated in favor of jie.


Why? What’s the difference from GSD, SuperPower?
  • Zero Dependency — just plain files.
  • Thin Skill Dispatchers — relentless context protection.
  • Idempotency — hussle-free resume with minimal state.
  • Hammered Specs — no surprise dev experience.
/gsd-autonomous /lissom-auto
GSD context LISSOM context
(Context after a 10m task on a small local model with Qwen Code)
When to use?
  • I have a scoped idea, help me refine the specs and automate the implementation.
When not to use?
  • Trivial or small tasks.
  • Exploratory tasks — use /explore.

Basic Workflow

           ┌─ interview ─┐
           │             /
 research ─┘ auto ──►   +   ──► plan ──► impl ──► review ──► done
  Specs.md    Research.md /    Plan.md         Review.md     │
   ▲                     /                                   │ critical?
   │                     └──────────── fix cycle (max 3)  ◄──┘
   │                                          │
   └──────────────── fix cycles exhausted ────┘

Installation

Install into your project’s directory with:

curl -fsSL https://raw.githubusercontent.com/cuzfrog/lissom-skills/main/scripts/install.sh | bash

Supported:

Uninstallation

Remove all installed files from the current project:

curl -fsSL https://raw.githubusercontent.com/cuzfrog/lissom-skills/main/scripts/uninstall.sh | bash

Only files originally installed by this bundle are removed — any custom files you added are left untouched. Empty directories are cleaned up automatically.


Here We Go!

Run /lissom-auto <task_id> — get interviewed and wait for the job done!

  1. It looks for the task in .lissom/tasks/<task_id>/Specs.md
  2. If not found, it tries to locate with tools (e.g. JIRA MCP)

Best practices

  • Don’t outsource your thinking. Review architecture and code structure. You should understand your code.
  • Use a simple grill-me skill to build the Specs.md. (mattpocock/skills)
  • Steer the behavior: /lissom-auto <task_id> Directly go to plan phase, I have a well-written spec already.
  • Define test methods (development cycle) clearly (e.g. in CLAUDE.md)

Configuration

Set preferences in .lissom/settings.local.json to avoid being asked each run:

{
  "user_attention": "default",
  "fix_threshold": "warning",
  "spec_review_required": false,
  "impl_delegation": "single"
}
Key Options
user_attention default — Interview for major concerns; auto — Best effort auto pilot; focused — Exhaustive questioning
fix_threshold warning — Fix critical & warnings; critical — Critical only; suggestion — All issues
spec_review_required false — Skip spec review; true — Review and refine specs before research
research_required true — Perform research before implementation; false — Skip research if the specs are already sufficient
impl_delegation single — Perform impl in one subagent (faster in most cases); multiple — Perform impl in multiple subagents (if impl scope is large; usually not necessary)

  • GitHub — source code and releases
  • Issues — bug reports and feature requests
  • License — MIT

Author

Cause Chung [email protected]

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