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agent-ready-codebaseAgent 就绪代码库

Agent Skill

agent-ready-codebase 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 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

4,187

周安装

178

GitHub Stars

11

下载量

1,467
CodexClaudeCursorGemini CLI

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

unknown

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:agent-ready-codebase(Agent 就绪代码库)
来源仓库:https://github.com/casper-studios/casper-marketplace
仓库路径:skills/agent-ready-codebase
安装命令:
npx skills add https://github.com/casper-studios/casper-marketplace --skill agent-ready-codebase
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/casper-studios/casper-marketplace --skill agent-ready-codebase

简介

评估代码库对 AI 代理友好度的五维指标体系与改进建议。

  • 基于环境、指令、校验分离等原则生成可操作的评分卡。
  • 适配不同语言栈并提供针对性优化路径说明。
  • 仅分析现有代码结构,不涉及运行时修改或外部调用。
  • agent-ready-codebase 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Agent-Ready Codebase

Overview

When agents struggle with a codebase, they are reflecting and amplifying the codebase's existing weaknesses. This skill evaluates codebases against five principles that determine agent effectiveness, and provides concrete guidance to improve each one. It adapts to the project's language and stack.

Based on "AI Is Forcing Us To Write Good Code".

Mode Selection

Determine which mode to operate in based on context:

  • Audit: The user has an existing codebase and wants to know where it stands. Evaluate all five principles and produce a scorecard with specific findings.
  • Guide: The user wants to improve a specific principle or set up a new project. Provide targeted, actionable steps for their stack.

If the mode is unclear, ask.

The Five Principles

  1. 100% Test Coverage -- Force every line of code to demonstrate its behavior with an executable example
  2. Thoughtful File Structure -- Make the filesystem a navigable interface for agents
  3. End-to-End Types -- Eliminate illegal states and shrink the agent's search space
  4. Fast, Ephemeral, Concurrent Dev Environments -- Keep feedback loops short and enable parallel agent workflows
  5. Automated Enforcement -- Remove degrees of freedom from the agent via linters, formatters, and hooks

Audit Workflow

To audit a codebase, work through these steps:

1. Detect the Stack

Identify the primary language, test framework, build system, and database by examining project files (e.g. package.json, go.mod, Gemfile, pyproject.toml, Cargo.toml). This determines which tooling recommendations apply.

2. Evaluate Each Principle

Read references/checklist.md for detailed criteria per principle. For each principle, determine the current state:

  • Test Coverage: Run or inspect coverage tooling. Look for CI enforcement. Report the current percentage and whether uncovered lines are identifiable.
  • File Structure: Sample the directory tree. Measure file sizes. Flag catch-all files (utils, helpers, common). Assess whether filenames communicate domain purpose.
  • Type System: Check for strict mode, semantic type names, API contract schemas, database constraints. Identify any/untyped gaps.
  • Dev Environments: Check for single-command setup, test suite runtime, port/DB isolation, worktree or container support.
  • Automated Enforcement: Check for linter/formatter configs, CI pipelines, git hooks, agent hooks.

3. Produce the Scorecard

Present findings as a table with one row per principle:

PrincipleRatingKey Finding
Test CoverageStrong / Adequate / Weake.g. "87% coverage, no CI enforcement"
File StructureStrong / Adequate / Weake.g. "3 files over 500 lines, 2 catch-all utils files"
TypesStrong / Adequate / Weake.g. "Strict TS, but no API schema generation"
Dev EnvironmentsStrong / Adequate / Weake.g. "Manual 8-step setup, no concurrent support"
EnforcementStrong / Adequate / Weake.g. "ESLint configured but not in CI"

4. Prioritize Improvements

Rank the weakest principles and suggest concrete next steps for the top 2-3. Each recommendation should reference the project's actual stack and tooling.

Guide Workflow

When guiding improvements to a specific principle:

  1. Read references/checklist.md for the relevant section
  2. Assess current state of that principle in the project
  3. Provide a concrete, ordered list of changes for the project's stack
  4. Where possible, show exact commands or config snippets

Key Insight: Why 100% Coverage

The most counterintuitive principle deserves emphasis. At 100% line coverage:

  • There is a phase change: uncovered lines are always from recent changes, removing all ambiguity about what needs testing
  • The coverage report becomes a simple todo list of tests still needed
  • It is not about proving "no bugs" -- it forces the author to demonstrate how every line behaves
  • Unreachable code surfaces immediately and gets deleted
  • Code reviews become easier because reviewers see concrete behavior examples
  • Once achieved, 100% is remarkably easy to maintain -- the coverage report enumerates exactly what lines need testing

Resources

references/

  • checklist.md -- Detailed evaluation criteria for each of the five principles, including stack-specific tooling, key indicators (Strong/Adequate/Weak), and guidance. Load this file when performing an audit or providing detailed guidance on any principle.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

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

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

Codex

33.59%
按下载量换算493

Claude

30.19%
按下载量换算443

Cursor

19.24%
按下载量换算282

Gemini CLI

8.49%
按下载量换算125

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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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