claude-code-research

作者 cablate已验证

Independent research on Claude Code internals, Claude Agent SDK, and related tooling.

153
Stars
64
Forks
HTML
语言
2026/8/23
添加时间

⚠️ 第三方软件声明

本 Skill 为第三方开源软件,独立托管于 GitHub。SkillTip 仅为信息目录,不控制或维护底层仓库。所显示的安全检查为自动化且范围有限,安装前请自行审查源码。

阅读服务条款

安装

添加到你的 Claude Code skills 目录:

# Add to your Claude Code skills
git clone https://github.com/cablate/claude-code-research

快速入门

使用 claude-code-research 等 Skills 的指南。

安全报告

已验证

上次扫描:—

{
  "status": "PASSED",
  "issues": []
}

README.md

Claude Code Research

Contributions Welcome

Independent research on Claude Code internals.

What's in this repo

DirectoryWhatSourceCount
source-code-analysis/Full architecture reverse-engineeringLeaked TypeScript source (v2.1.88)75 reports
reports/Problem-oriented investigations (cache, cost, injection)Minified npm bundle (cli.js)8 reports

Looking for the source code analysis? Go to source-code-analysis/. Looking for specific bug/cost investigations? Go to reports/.


Source Code Analysis (source-code-analysis/)

On 2026-03-31, the full source code of Claude Code was exposed via a sourcemap file in the npm registry (discovered by Chaofan Shou, archived by Kuberwastaken and sanbuphy).

We performed a 10-domain, 75-report analysis — the most thorough publicly available breakdown of how a production AI coding agent works.

Browse all reports →

Interactive viewer — open source-code-analysis/index.html in your browser (all 75 reports are embedded, no server needed).

Key Findings

DomainReportsHighlights
Harness Engineering7Agent Loop reverse-engineering, 12 transferable harness design principles
System Prompt6Complete 13-section prompt with dynamic assembly logic, 17 prompt engineering patterns
Cost & Quota8Cost envelope, prompt cache break detection (12 causes), Haiku→Opus 37.5x cost gap
Tool Definitions8All 36 tool prompts, read/write concurrency separation, ant vs public prompt variants
Agent Architecture76 built-in agents, Coordinator mode, Swarm multi-agent, 50-message cap (from 36.8GB incident)
Security87-layer defense-in-depth, 23 Bash validators, Parser Differential threat model
Skills System516 bundled skills, 12 design patterns + 5 anti-patterns
Memory & Context96 memory subsystems, AutoDream consolidation, Team Memory dual-layer security
API & Models717 beta headers, 4 providers, model selection 5-layer priority
Hidden Features1082 feature flags, KAIROS proactive mode, Buddy AI pet, UltraPlan, anti-distillation

Behavioral Reports (reports/)

Problem-oriented investigations based on reverse engineering the minified cli.js from npm. Each includes English and Chinese versions.

#TopicTL;DR
1Agent SDK Cache InvalidationSDK query() costs 3–10x more than CLI — process-per-call kills prompt cache
2System-Reminder Injection15+ hidden injection types, 4 root-cause bugs
3Prompt Cache ArchitectureStatic/dynamic zone split, sliding window, byte-prefix matching
4Tool Serialization & Cache StabilityZero .sort() on tools, deferred loading busts cache mid-conversation
5Context Lifecycle Management5 threshold constants, 10-step compaction flow, chain reactions
6Production Cache Optimization3 concrete cli.js patches + monitoring strategies
7Cache Invalidation Verificationdefer_loading excludes deferred tools from cache prefix entirely
8Auto Mode Classifier CostHidden Opus-level call before every side-effecting tool use

Resources

Source Code Archives

The analysis is based on the full TypeScript source of Claude Code v2.1.88. The source code itself is not included in this repo.

Version Baseline

ScopeVersion
Source Code Analysisv2.1.88 (sourcemap leak, 2026-03-31)
Behavioral Reports #1–2v2.1.71
Behavioral Reports #3–6Agent SDK v0.2.76 (build 2026-03-14)
Behavioral Reports #7–8v2.1.85 / v2.1.88

How to Cite

CabLate, "Claude Code Research," GitHub, 2026.
https://github.com/cablate/claude-code-research

Disclaimer

This is independent research, not affiliated with or endorsed by Anthropic. Behavioral reports analyze publicly distributed npm packages. Source code analysis is based on code exposed through npm registry sourcemaps.

常见问题

What is claude-code-research?

claude-code-research is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by cablate. Independent research on Claude Code internals, Claude Agent SDK, and related tooling. It has 153 GitHub stars.

Is claude-code-research safe to use?

Yes. claude-code-research passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.

How do I install claude-code-research?

Clone the repository with "git clone https://github.com/cablate/claude-code-research" and add it to your Claude Code skills directory (see the Installation section above).

What programming language is claude-code-research written in?

claude-code-research is primarily written in HTML. It is open-source under cablate on GitHub, so you can review or fork the full source.

Are there alternatives to claude-code-research?

Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh claude-code-research against similar tools.

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