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Agent Skill · 开发

lev-intake(左旋摄入量)

lev-intake 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

lev-intake 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描有未通过项,按安装量在开发类的 21,746 个 Skill 里排第 19,716。

总安装 259周安装 11GitHub Stars 2下载 91核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:lev-intake(左旋摄入量)
来源仓库:https://github.com/lev-os/agents
仓库路径:skills/lev-intake
安装命令:
npx skills add https://github.com/lev-os/agents --skill lev-intake
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/lev-os/agents --skill lev-intake

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

lev-intake 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。适用于代码审查、项目进度跟踪和团队协作事项管理等开发协作场景。

通过 npx skills add 命令从指定 GitHub 仓库安装,需确认权限范围和联网需求。建议结合原始 README 核验具体用法,注意维护状态及是否触发文件读写操作。lev-intake 属于开发类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/lev-intake

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/lev-os/agents --skill lev-intake;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

lev-intake 怎么安装?

在终端执行 npx skills add https://github.com/lev-os/agents --skill lev-intake。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

lev-intake 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

lev-intake 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

lev-intake 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

lev-intake 用的人多吗?

公开数据是累计安装 259 次,近一周安装 11 次,下载 91 次,GitHub 2 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

lev-intake 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
lev-intake

左旋摄入量 · 本页

2592只读未明确未通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Config-Driven Workshop Intake

Use this skill to intake external material for the active project while honoring global workshop compatibility when explicitly configured.

Primary Rule

Never hardcode workshop paths.

Always resolve:

  1. active project root
  2. merged workshop config
  3. workshop manifest
  4. configured playbooks

Role

You are a project-grounded intake analyst.

You:

  • acquire external material cleanly
  • compare it to the active project's actual needs
  • preserve workshop compatibility through config overlays
  • recommend the smallest useful disposition

Phase 0: Resolve Project + Workshop Context

Execute these steps first:

0.1 Resolve project root

  • git rev-parse --show-toplevel

Set:

  • PROJECT_ROOT=<git root>

0.2 Load overlay config

Read, in this order:

  • global: ~/.config/lev/config.yaml
  • project: <projectRoot>/.lev/config.yaml

Merge the workshop: section with project values overriding global values.

0.3 Resolve workshop paths

Use this resolution order:

  1. workshop.root

- if absolute, use as-is - if relative, resolve from PROJECT_ROOT - if missing, default to <projectRoot>/.lev/workshop

  1. workshop.manifest

- if set, resolve it - else default to <workshopRoot>/manifest.yaml

  1. workshop.reports.intake

- if set, use it - else default to <projectRoot>/.lev/pm/intake

  1. workshop.playbooks.repo_intake
  2. workshop.playbooks.papers_intake

0.4 Load manifest if present

If <workshopManifest> exists, load it and use it to resolve folder names such as:

  • intake
  • analysis
  • approved
  • extract
  • cache
  • papers
  • reports
  • transcripts
  • reference

If no manifest exists, default folder names are:

  • intake
  • analysis
  • approved
  • extract
  • cache
  • papers
  • reports
  • transcripts
  • _ref

0.5 Load project docs

Required:

  • <projectRoot>/AGENTS.md

Preferred:

  • <projectRoot>/docs/NORTH_STAR.md
  • <projectRoot>/docs/01-architecture.md
  • <projectRoot>/docs/00-process.md

If the project-specific context paths are configured under workshop.context, use those first.

Fail fast only if:

  • AGENTS.md is missing, or
  • there is no usable architecture/direction source at all

0.6 Load relevant local skills

If project-local skills are relevant, load them before analysis.

Example:

  • OpenClaw-adjacent repo inside KinglyAssistant → load <projectRoot>/.agents/skills/openclaw/SKILL.md

KinglyAssistant Defaults

If the active project is KinglyAssistant / ClawBuddy, the expected defaults are:

  • workshop root: .lev/workshop/
  • workshop manifest: .lev/workshop/manifest.yaml
  • intake reports: .lev/pm/intake/
  • guide: AGENTS.md
  • product direction: docs/NORTH_STAR.md
  • architecture: docs/01-architecture.md
  • process: docs/00-process.md

For KinglyAssistant, evaluate external work against:

  • macOS installer and gateway lifecycle
  • iOS chat, voice, pairing, and session UX
  • shared Swift packages and test harnesses
  • OpenClaw wrapper/integration strategy
  • ClawBuddy/companion UX and product polish
  • bundles, marketplace, and tooling

Phase 1: Acquire Content

URL Detection

If no URL is provided, ask for one.

If provided, classify as:

  • GitHub repo
  • video/media
  • article/documentation
  • skills.sh / skill package
  • skill://

GitHub Repository

Clone into:

  • <workshopRoot>/<folders.intake>/<repo_name>

Then:

  • verify with ls -la
  • identify top-level structure
  • identify stack + test/build entrypoints

Video / Media

Route through:

  • ~/digital/homie/yt/cli.py
  • fallback ~/digital/homie/yt/yt.py

Save transcript to:

  • <workshopRoot>/<folders.intake>/<slug>/transcript.md

Article / Documentation

Route through:

  • local scraper first
  • web scrape fallback second

Save content to:

  • <workshopRoot>/<folders.intake>/<slug>/article.md

Skill Package / skill://

Route installation lifecycle to skill-builder when installation is actually needed.

This skill's job is relevance assessment for the active project.

Phase 2: Analyze

If a repo-intake playbook is configured

If workshop.playbooks.repo_intake is set and exists:

  • load it
  • follow it after acquisition

If a papers-intake playbook is configured

If the target is paper/media heavy and workshop.playbooks.papers_intake is set:

  • load it
  • follow it for paper-oriented analysis

If no playbook is configured

Analyze against the active project's own docs and structure.

Required reads:

  • project guide
  • north star if present
  • architecture if present
  • process doc if present
  • target repo README
  • package/manifest files
  • 3-5 core implementation files

Answer with evidence:

  1. What problem does this solve?
  2. Which part of the active project does it map to?
  3. Is it product, infrastructure, integration, or tooling?
  4. Does it conflict with current architecture or constraints?
  5. Is the value in adoption, extraction, monitoring, or simple awareness?

Recommended Multi-Agent Split

Use sub-agents in parallel when practical:

  • context-scan: project docs + architecture + tier mapping
  • repo-scan: target repo purpose, stack, capabilities
  • fit-scan: overlap, gaps, and disposition

Each sub-agent must return:

  • executive brief
  • manifest of files touched
  • saved report path only if detail would exceed 5000 tokens

Phase 3: Disposition

Use project-specific decisions:

  • integrate

- strong fit for roadmap or architecture

  • extract

- valuable patterns, not a direct dependency

  • monitor

- interesting, not aligned enough right now

  • pass

- low fit or redundant

  • vendor

- near-term explicit reason to vendor code into vendor/

Output Artifacts

Write the final report to:

  • <resolved report dir>/<slug>-intake.md

The report must include:

  • target URL
  • resolved project root
  • resolved workshop root
  • resolved manifest path
  • configured playbook inputs
  • staged source path
  • project context used
  • decision
  • rationale
  • next action

Output Template

# Intake Report: <name>

- URL: <url>
- Type: <repo|video|article|skill>
- Project Root: <project root>
- Workshop Root: <workshop root>
- Workshop Manifest: <manifest path or missing>
- Repo Playbook: <path or null>
- Papers Playbook: <path or null>
- Staged Source: <path>
- Report Path: <path>

## Project Context
- Guide: <path>
- North Star: <path or missing>
- Architecture: <path or missing>
- Process: <path or missing>

## External Summary
- Purpose:
- Stack:
- Key capabilities:

## Fit For Current Project
- Surface:
- Tier:
- Relevant overlaps:
- Conflicts:

## Decision
- Decision:
- Why:
- Recommended next step:

Success Criteria

  • Workshop paths come from merged config, not hardcoded defaults
  • Manifest-driven folder resolution works when present
  • Legacy Lev workflow remains possible through global config
  • Project-local workshop defaults work when no global override exists
  • Report is written to the configured report destination

Notes

  • For Lev itself, set workshop.root to ~/lev/workshop and point playbooks at the existing intake.md / papers/intake.md.
  • For project repos, default to <projectRoot>/.lev/workshop.
  • A checked-in workshop manifest plus gitignored runtime folders is the intended shape for project-local workshop state.

平台分布

Codex

37.3%
按下载量换算34

Claude

30%
按下载量换算27

Cursor

19.56%
按下载量换算18

Gemini CLI

9.02%
按下载量换算8

安全审计

Gen Agent Trust Hub

未通过

Socket

可疑

Snyk

未通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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