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lean-claude-code-harnesslean Claude 代码 harness

Agent Skill

lean-claude-code-harness 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

总安装

5,239

周安装

214

GitHub Stars

公开资料未说明

下载量

1,678
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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:lean-claude-code-harness(lean Claude 代码 harness)
来源仓库:https://github.com/aznikline/lean-claude-code-harness
安装命令:
openclaw skills install lean-claude-code-harness
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install lean-claude-code-harness

简介

优化 AI 编码代理工具配置与权限管理机制。

  • 特别适用于运行时配置不明确时的审核与简化操作。
  • 帮助提升工具链安全性与执行效率。lean-claude-code-harness 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 安装命令:openclaw skills install lean-claude-code-harness。
  • 需评估当前工具权限是否足以支撑其运行需求。

SKILL.md

name
lean-claude-code-harness
description
Use when building, auditing, or simplifying an AI coding-agent harness, especially when the current runtime has unclear config precedence, weak tool permissions, hidden product-only behavior, or poor transcriptability.
metadata

Lean Claude Code Harness

Distill the durable parts of Claude Code into a smaller, auditable harness. The goal is not feature parity. The goal is a runtime another engineer can understand, extend, and verify without reverse-engineering hidden behavior.

When to Use

Use this skill when a coding-agent runtime shows any of these symptoms:

  • config values are hard to trace
  • tool permissions are implicit or inconsistent
  • the tool surface keeps growing without clear ownership
  • session history disappears after a run
  • the main loop is hard to sketch from memory
  • product-only logic is mixed into the harness core

Keep These Primitives

  • layered configuration
  • permission-aware tool execution
  • a small explicit tool registry
  • markdown skill discovery
  • transcript persistence
  • a visible query loop

Remove These By Default

  • telemetry
  • remote-managed settings
  • hidden kill-switches
  • private feature flags
  • branding-specific branches
  • heavyweight UI layers

Only add them back when the user explicitly asks for them and can explain the operational need.

Quick Audit

If you need a fast harness review, answer these six questions first:

  1. Can you explain config precedence without reading three files?
  2. Are tool permissions checked before execution?
  3. Can you list the built-in tools in one screen?
  4. Are skills discovered from visible files instead of hidden registration?
  5. Does every run persist a transcript?
  6. Can you trace the query loop from prompt to final response?

If two or more answers are "no", the harness is already too opaque.

Apply This Order

1. Freeze the Runtime Boundary

Keep the entrypoint thin. It should only:

  • parse commands
  • load merged config
  • wire services
  • print results

Do not hide business logic in the CLI layer.

2. Make Config Precedence Explicit

Use a predictable merge order:

  1. defaults
  2. user config
  3. project config
  4. local config
  5. environment overrides

If a runtime value cannot be traced back to one of these sources, the harness is already drifting into opacity.

3. Gate Tools Before Execution

Define permission policy before the query loop runs tools.

Minimum pattern:

  • default and plan expose read-only tools
  • write or shell tools require a stronger mode
  • bypassPermissions should be explicit and rare

Permission checks belong before tool execution, not after damage is already possible.

4. Start with a Tiny Tool Surface

Default tool set should be boring and legible:

  • list_files
  • read_file
  • grep
  • bash

Do not add tools because the upstream product has them. Add tools only when they expand capability without making the harness harder to reason about.

5. Keep Skills File-Backed

Discover skills from SKILL.md files with frontmatter metadata. Avoid hidden registration layers, magic imports, or remote skill switches.

The discovery rule should be explainable in one sentence: scan configured directories, parse frontmatter, expose name, description, and path.

6. Persist Every Session

Save transcripts to disk. Each transcript should include:

  • session id
  • timestamp
  • prompt
  • tool steps
  • final response

If an agent run cannot be inspected afterward, debugging and trust both degrade.

7. Keep the Query Loop Visible

The harness should make this loop easy to trace:

  1. receive prompt
  2. ask provider for next action
  3. validate tool request
  4. execute tool
  5. append tool result to state
  6. repeat until final response
  7. persist transcript

If you cannot sketch the loop from memory, the runtime is already too opaque.

Anti-Patterns

  • cloning upstream complexity without upstream context
  • mixing config loading, permission logic, and tool execution in one file
  • treating remote flags as architecture instead of distribution policy
  • adding analytics before the harness can explain itself locally
  • claiming a harness is complete without transcript and permission tests

Minimal Verification

Before calling the harness usable, verify:

  • config precedence behaves as documented
  • permission modes actually filter tools
  • skill discovery finds real SKILL.md files
  • session persistence writes and reloads transcripts
  • the full query loop works with a deterministic provider

The verification standard is simple: no claims about the harness until the config, permission, skills, session, and loop seams are each exercised once.

Use This Skill To

  • design a fresh coding-agent harness
  • simplify a bloated Claude Code-style runtime
  • review an existing agent runtime for opacity and unnecessary layers
  • extract reusable harness patterns from a larger codebase

Do Not Use This Skill To

  • recreate the full Claude Code product surface
  • justify hidden behavior with “that is how the upstream does it”
  • add cloud control planes, telemetry, or feature flags without a concrete requirement

Output Standard

When applying this skill, produce:

  • the minimal harness shape
  • the layers kept vs removed
  • the exact config precedence
  • the permission model
  • the smallest verification plan that proves the harness is real

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

82.44%
按下载量换算1,383

安全审计

VirusTotal

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ClawScan

通过

Static analysis

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权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install lean-claude-code-harness 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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