ClawCodex

ClawCodex

A production-oriented Python rebuild of Claude Code — real architecture, reliable CLI agent

Ported from the TypeScript reference implementation and extended with a Python-native runtime

🔥 Active Development • New Features Weekly 🔥

🐋🔥 DeepSeek Prefix Cache

Run long agentic coding sessions for pennies

Cache-hit input bills at `~$0.0435` / 1M tokens — about 230× cheaper than Claude Fable 5 (`$10` / 1M).

ClawCodex keeps your request prefix byte-stable, so DeepSeek's prompt cache covers your whole system + tools + history span across turns. The longer you code, the more you save.

⚡ Quick Install

git clone https://github.com/agentforce314/clawcodex.git
cd clawcodex
python3 -m venv .venv && source .venv/bin/activate   # Python 3.10+
pip install -r requirements.txt

python -m src.cli login   # writes config to ~/.clawcodex/config.json

python -m src.cli --dangerously-skip-permissions   # start the REPL

The configuration file is saved at ~/.clawcodex/config.json. Minimal example:

{
  "default_provider": "deepseek",
  "providers": {
    "deepseek": {
      "api_key": "xxx-xxx",
      "base_url": "https://api.deepseek.com",
      "default_model": "deepseek-v4-pro"
    }
  },
  "env": {
    "TAVILY_API_KEY": "tvly-YOUR-TAVILY-API-KEY"
  }
}

Note: TAVILY_API_KEY is required for the WebSearch tool — get a key at tavily.com.

The session, settings, and env blocks are optional — sensible defaults apply when they're omitted. See Configure for the full structure.

📰 News

2026-06-18: DeepSeek prefix-cache exploitation — a HUGE token-cost win (#363) — ClawCodex now keeps its request prefix byte-stable across turns so DeepSeek's automatic prompt-prefix cache covers the entire system + tools + history span. Per-request-volatile sections (env, the mutable MEMORY.md body, plan-mode, etc.) are relocated to a trailing <system-reminder> after the conversation history, so the cached prefix never breaks even when memory/env change. We also register DeepSeek's 1M-token context window, map its prompt-cache usage onto the Anthropic cache_read_input_tokens convention, and surface a per-model prompt-cache hit-rate + cost in /cost. Why this is enormous — the token economics: Claude Fable 5 runs $10 / $50 per 1M input/output tokens, while DeepSeek-V4-Pro is just $0.435 / $0.87 — already ~23× cheaper on input and ~57× cheaper on output. And because cache-hit input is billed at only 10% of the normal input rate, the long, context-heavy sessions that agentic coding actually produces pay just ~$0.0435 per 1M input tokens — roughly 230× cheaper than Fable 5 input. The token efficiency ClawCodex unlocks here is HUGE. Everything is gated to the deepseek provider — every other provider's request is byte-for-byte unchanged. Follow-up: truncated tool-call argument JSON is now best-effort recovered in the shared OpenAI-compatible layer, so an interrupted DeepSeek stream keeps its partial tool args instead of dropping them to {} (#364).
2026-06-16: Z.ai GLM-5.2 support (#343) — new zai provider for Z.ai's OpenAI-compatible GLM Coding Plan (https://api.z.ai/api/coding/paas/v4), shipping GLM-5.1 and the GLM-5.2 preview; GLM-5.2 delivers coding capability comparable to Claude Opus 4.7. First app built end-to-end with GLM-5.2 — a FIFA World Cup 2026 intro page (animated hero + live countdown, three host nations, 16 stadiums, tournament format, and record-breaking facts).
2026-06-11: Codebase stats — Total Python files: 1,093 files; Total Lines of Python Code: 233,520 lines (up from 213,777 lines on 2026-05-29; ~+19.7k lines from the interactive command-system batch, the dynamic workflow engine + /deep-research, and the Tavily web-tooling refresh).
2026-06-10 to 2026-06-11: Dynamic workflow engine + /deep-research (#262–#264, #266–#271) — Python workflow engine core (agent()/parallel()/pipeline()/phase(), journaling, resume) wired end-to-end: Workflow tool, /workflows TUI dialog + status-line pill, per-agent retry, worktree isolation, result delivery, and the bundled /deep-research harness registered as a slash command. Reliability: LLM read timeout applied centrally to all openai-compatible providers (#269), parallel agents no longer serialize on the event loop (#270), and the deep-research synthesize step forbids tools so the report-writer can't loop (#271). Follow-ups: workflow max-turns cap fix (#272), deep-research verdict-enum fix (#273), rich /workflows live monitor with phase progress + per-agent stats (#287).
2026-06-10: Web tooling refresh (#265) — dead DuckDuckGo scraping replaced with a Tavily-backed WebSearch plus config-backed secrets storage; WebFetch rebuilt with deterministic markdown/text/html extraction (borrowed from opencode).
2026-05-30 to 2026-06-09: Interactive command-system parity (#230–#261) — interactive ports of /theme, /effort, /model, /logo, /mcp, /tasks, /diff, /export, /output-style, /statusline, /release-notes, /copy, /vim, /memory, /stickers, and /rename, built on a new prompt-text primitive and interactive command bridge; skill registration and model tool-exposure wiring; the session-persistence producer (SessionPersister + agent-bridge wiring); plus extended thinking support (#249) and a model error-swallow fix (#250).
2026-05-29: Codebase stats — Total Python files: 977 files; Total Lines of Python Code: 213,777 lines (up from 183,768 lines on 2026-05-21; ~+30k lines from the remote-bridge parity port (phases 0–18) plus the /buddy companion subsystem and the CLI transport layer).
2026-05-29: Remote-bridge parity + CLI transports (#200–#226) — full port of the remote-control bridge across phases 0–18: bridge API client, child-CLI session runner, env-less v2 orchestrator, multi-session daemon, worktree spawn, in-place reconnect, perpetual mode with crash recovery, JWT refresh, and the v1 WebSocketTransport / SerialBatchEventUploader write path with hybrid dispatch. Plus the CLI transport factory, coalescing worker-state uploader, and RemoteIO bridge (#226); new /buddy virtual-companion command — hatch / pet / status / mute (#225).
2026-05-21: Codebase stats — Total Python files: 890 files; Total Lines of Python Code: 183,768 lines (up from 177,428 lines on 2026-05-16; net −4 files from the src/tool_system/agent_loop.py consolidation into src/query/query.py).
2026-05-21: /advisor token-efficient coding mode (#181–#193) — pair a cheap worker (haiku-4-5, $1/$5 per Mtok) with an expensive reviewer (opus-4-7, $5/$25) consulted only at decision points; ~6× cheaper than opus-only on typical sessions. Explicit <provider>:<model> syntax, cross-provider routing (e.g. deepseek/deepseek-v4-pro worker + claude-opus-4-7 advisor via litellm), and live worker/advisor token + USD cost in the status bar.
2026-05-16: Codebase stats — Total Python files: 894 files; Total Lines of Python Code: 177,428 lines (up from 167,034 lines on 2026-05-14; ~+10.4k lines in two days, mostly ESC-cancellation hardening + image-handling parity).

📚 Older items have moved to the full News archive.

🎯 Why ClawCodex?

ClawCodex is a production-oriented Python rebuild of Claude Code, ported from the real TypeScript architecture and shipped as a working CLI agent, not just a source dump.

Real Agent Runtime — tool-calling loop, streaming REPL, session history, and multi-turn execution
High-Fidelity Port — keeps the original Claude Code architecture while adapting it to idiomatic Python
Built to Hack On — readable Python codebase, rich tests, and markdown-driven skill extensibility
Multi-LLM providers — the biggest step forward vs. upstream: Claude Code is built around Claude-series models only; ClawCodex is dedicated to wiring in all major LLM providers so you can choose the most flexible and cost-effective stack for agentic coding

A real Claude Code-style terminal workflow in Python: stream replies, call tools, fetch context, and extend behavior with skills.

🚀 Try it now! Fork it, modify it, make it yours! Pull requests welcome!

🏆 SWE-bench Verified — `clawcodex` outperforms `openclaude` on the same model

On the full SWE-bench Verified split (499 instances, the public agent-coding leaderboard), both agents driven by Gemini 2.5 Pro under our standardized harness:

Agent	Resolved	Unresolved	Error
clawcodex	291 / 499 (58.2%)	124	84
openclaude	265 / 499 (53.0%)	144	90

✅ Both solved: 241 🟢 Only clawcodex: 50 🔵 Only openclaude: 24 ❌ Neither: 184

Reproduce locally — see eval/README.md for the full workflow (cumulative batching, --predict-workers N, --capture-traces).

⭐ Star History

View star history on star-history.com

✨ Features

Streaming Agent Experience

>>> /stream on
>>> Explain tests/test_agent_loop.py
[streaming answer...]
• Read (tests/test_agent_loop.py) running...
  ↳ lines 1-180
>>> /render-last

True API streaming for direct replies plus richer streaming during tool-driven agent loops
Built-in /stream toggle for live output and /render-last for clean Markdown re-rendering on demand
Designed for real terminal demos: streaming text, visible tool activity, and stable fallback behavior

Programmable Skill Runtime

---
description: Explain code with diagrams and analogies
allowed-tools:
  - Read
  - Grep
  - Glob
arguments: [path]
---

Explain the code in $path. Start with an analogy, then draw a diagram.

Markdown-based SKILL.md slash commands
Supports project skills, user skills, named arguments, and tool limits

Multi-Provider Support

ClawCodex’s main advantage is multi-provider support: while Claude Code targets Claude models, we aim to support every major LLM provider behind the same agent runtime—so you can swap vendors, regions, and price tiers without giving up tools, skills, or the coding loop. That flexibility is what makes agentic coding practical at scale.

providers = ["anthropic", "openai", "zai", "minimax", "openrouter", "deepseek"]  # OpenAI-compatible & GLM APIs; more can be added

Interactive REPL (default) and Textual TUI (opt-in)

The default interactive UI is the inline prompt_toolkit + Rich REPL (transcript in scrollback, tool-aware status row). Use clawcodex --tui or the /tui slash command inside the REPL to launch the Textual in-app experience when you want it.

>>> Hello!
Assistant: Hi! I'm ClawCodex, a Python reimplementation...

>>> /help          # Show commands
>>> /tools         # List registered tools
>>> /tui           # Hand off to the Textual TUI
>>> /stream on     # Live response rendering
>>> /save          # Save session
>>> Tab            # Auto-complete
>>> /explain-code qsort.py   # Run a SKILL.md skill (or /skill …)

# Multi-line input: Shift+Enter, Meta/Alt+Enter, or `\` then Enter for newline; plain Enter submits.

Complete CLI

clawcodex                       # Inline REPL (default)
clawcodex --tui                 # Textual TUI
clawcodex --stream              # REPL with live rendering
clawcodex login                 # Configure API keys (interactive)
clawcodex config                # Show ~/.clawcodex/config.json-backed settings
clawcodex --version             # Version string

# Non-interactive / scripting (pipes, CI, agents)
clawcodex -p "Summarize src/cli.py"
clawcodex -p "Hello" --output-format json
clawcodex -p --output-format stream-json --input-format stream-json < events.ndjson

# Overrides for a single run
clawcodex --provider anthropic --model claude-sonnet-4-6 -p "Hi"
clawcodex --max-turns 10 --allowed-tools Read,Grep -p "Find TODOs"

# Permission control (REPL, TUI, and -p all honor these)
clawcodex --permission-mode plan                       # plan / acceptEdits / dontAsk
clawcodex --dangerously-skip-permissions -p "ls"       # bypass all permission checks
clawcodex --allow-dangerously-skip-permissions         # allow /permission-mode bypass later

--dangerously-skip-permissions disables every tool permission check for the session. Recommended only inside sandboxed containers/VMs with no internet access. The flag is refused when the process is running as root/sudo unless IS_SANDBOX=1 or CLAUDE_CODE_BUBBLEWRAP=1 is set.

📊 Status

Component	Status	Count
REPL Commands	✅ Complete	Built-ins + `/tools`, `/stream`, `/context`, `/compact`, skills, etc.
Tool System	✅ Complete	30+ tools
Automated Tests	✅ Present	Tools, agent loop, providers, parity, REPL, auth, and more
Documentation	✅ Complete	Guides, i18n READMEs, FEATURE_LIST.md

Core Systems

System	Status	Description
CLI Entry	✅	`clawcodex`, `login`, `config`, `-p` / `--print`, `--tui`, `--stream`, `--version`
Interactive REPL	✅	Default inline REPL; optional Textual TUI; history, tab completion, multiline
Multi-Provider	✅	Anthropic, OpenAI, Z.ai GLM, Minimax, OpenRouter, DeepSeek — including Anthropic→OpenAI image / document block translation for vision-capable OpenAI-compat backends
Session Persistence	✅	Save/load sessions locally
Agent Loop	✅	Tool calling loop with streaming and headless mode
Skill System	✅	SKILL.md-based slash-command skills with args + tool limits
Cancellation / Abort	✅	ESC closes in-flight Bash, Grep/Glob, and streaming HTTP within ~50ms across every provider; subagents get isolated `AbortController`s; `Bash` `tool_result` distinguishes timeout from ESC-abort
Image Handling	✅	TS-parity Read pipeline (magic-byte sniff, resize/compress to API limits); `@image.png` @-mentions inline as `ImageBlock`; pre-API base64 size validation in `BaseProvider._prepare_messages`; binary @-mentions (PDF/zip/docx/...) routed to a Read-tool hint instead of mojibake
Context Building	🟡	Workspace / git / `CLAUDE.md` injection; richer summaries and memory still evolving
Permission System	🟡	Framework and checks; full integration still in progress
MCP	🟡	MCP-oriented tools and wiring; full protocol/runtime polish ongoing

Tool System (30+ Tools Implemented)

Category	Tools	Status
File Operations	Read, Write, Edit, Glob, Grep	✅ Complete
System	Bash execution	✅ Complete
Web	WebFetch, WebSearch	✅ Complete
Interaction	AskUserQuestion, SendMessage	✅ Complete
Task Management	TodoWrite, TaskManager, TaskStop	✅ Complete
Agent Tools	Agent, Brief, Team	✅ Complete
Configuration	Config, PlanMode, Cron	✅ Complete
MCP	MCP tools and resources	🟡 Tools wired; full client/runtime still evolving
Others	LSP, Worktree, Skill, ToolSearch	✅ Complete

Roadmap Progress

✅ Phase 0: Installable, runnable CLI
✅ Phase 1: Core Claude Code MVP experience
✅ Phase 2: Real tool calling loop
🟡 Phase 3: Context depth, permission integration, /resume-class recovery (in progress)
🟡 Phase 4: MCP runtime depth, plugins, extensibility (tools exist; platform work continues)
⏳ Phase 5: Python-native differentiators

See FEATURE_LIST.md for detailed feature status and PR guidelines.

🚀 Quick Start

Install

git clone https://github.com/agentforce314/clawcodex.git
cd clawcodex

# Create venv (uv recommended)
uv venv --python 3.11
source .venv/bin/activate

# Install package + entry point (recommended)
uv pip install -e ".[dev]"

# Alternative: requirements only, then editable install
# uv pip install -r requirements.txt && uv pip install -e .

Configure

Option 1: Interactive (Recommended)

clawcodex login
# or: python -m src.cli login

This flow will:

ask you to choose a provider: anthropic / openai / zai / minimax / openrouter / deepseek
ask for that provider's API key
optionally save a custom base URL
optionally save a default model
set the selected provider as default

The configuration file is saved in ~/.clawcodex/config.json. Example structure:

{
  "default_provider": "deepseek",
  "providers": {
    "anthropic": {
      "api_key": "your-api-key",
      "base_url": "https://api.anthropic.com",
      "default_model": "claude-sonnet-4-6"
    },
    "openai": {
      "api_key": "your-api-key",
      "base_url": "https://api.openai.com/v1",
      "default_model": "gpt-5.4"
    },
    "zai": {
      "api_key": "your-api-key",
      "base_url": "https://api.z.ai/api/coding/paas/v4",
      "default_model": "glm-5.2"
    },
    "minimax": {
      "api_key": "your-api-key",
      "base_url": "https://api.minimaxi.com/anthropic",
      "default_model": "MiniMax-M2.7"
    },
    "openrouter": {
      "api_key": "your-api-key",
      "base_url": "https://openrouter.ai/api/v1",
      "default_model": "deepseek/deepseek-v4-pro"
    },
    "deepseek": {
      "api_key": "your-api-key",
      "base_url": "https://api.deepseek.com",
      "default_model": "deepseek-v4-pro"
    }
  },
  "session": {
    "auto_save": true,
    "max_history": 100
  },
  "settings": {
    "advisor_enabled": false,
    "advisor_model": "claude-sonnet-4-6",
    "advisor_client_mode": false,
    "advisor_provider": "openai"
  },
  "env": {
    "TAVILY_API_KEY": "tvly-YOUR-TAVILY-API-KEY"
  }
}

session — REPL session persistence: auto_save writes each session automatically; max_history caps retained turns.
settings — the advisor (reviewer) feature. advisor_enabled is the master switch — false by default, so the advisor is OFF unless you opt in (set it to true, or run /advisor <provider>:<model> which flips it on). advisor_provider / advisor_model pick the reviewer model; advisor_client_mode routes the call via the client.
env — secrets and environment values injected at startup (e.g. TAVILY_API_KEY for web search). Managed via clawcodex config; keys here are exported into the process environment without overriding anything you already set in your shell.

Run

clawcodex                  # Start inline REPL (same as python -m src.cli)
clawcodex --help           # All flags: --tui, -p, --provider, --model, …

That's it! Configure keys, then run the CLI or REPL.

💡 Usage

REPL Commands

Command	Description
`/`	Show commands and skills
`/help`	Help text
`/tools`	List tool names from the registry
`/tool <name> <json>`	Run a tool directly with JSON input
`/stream`	Toggle streaming: `/stream on`, `off`, or `toggle`
`/render-last`	Re-render last assistant reply as Markdown
`/save` / `/load <id>`	Persist or restore a session
`/clear`	Clear conversation (also `/reset`, `/new`)
`/tui`	Switch to the Textual TUI
`/skill`	Skill launcher flow
`/context`	Workspace / prompt context (when available)
`/compact`	Compact or clear conversation (fallback clears if compact unavailable)
`/exit`, `/quit`, `/q`	Exit

Skills (Slash Commands)

Skills are markdown-based slash commands stored under .clawcodex/skills. Each skill lives in its own directory and must be named SKILL.md.

1) Create a project skill

Create:

<project-root>/.clawcodex/skills/<skill-name>/SKILL.md

Example:

---
description: Explains code with diagrams and analogies
when_to_use: Use when explaining how code works
allowed-tools:
  - Read
  - Grep
  - Glob
arguments: [path]
---

Explain the code in $path. Start with an analogy, then draw a diagram.

2) Use it in the REPL

❯ /
❯ /<skill-name> <args>

Example:

❯ /explain-code qsort.py

Notes

User-level skills: ~/.clawcodex/skills/<skill-name>/SKILL.md
Tool limits: allowed-tools controls which tools the skill can use.
Arguments: use $ARGUMENTS, $0, $1, or named args like $path (from arguments).
Placeholder syntax: use $path, not ${path}.

🎨 Demos

Every app under demos/ was generated end-to-end by ClawCodex itself — same CLI you just installed, same agent loop, same tools. No hand-edits 🙂

Demo	Stack	Description
`demos/crm-app`	React 18 + Vite + Vitest	Mini CRM with contacts, deals, dashboard, and a full test suite
`demos/linkedin-app`	React 18 + Vite + React Router	LinkedIn-style feed: profile, network, jobs, messaging
`demos/minecraft-app`	React + three.js + @react-three/fiber	Browser voxel sandbox with terrain, mining, HUD, and player controls
`demos/wc26-intro`	Static HTML/CSS/JS	FIFA World Cup 2026 intro page — animated hero, live countdown, host nations, 16 stadiums, format, and record facts; built end-to-end with the new Z.ai GLM-5.2 model

cd demos/crm-app   # or linkedin-app / minecraft-app
npm install
npm run dev        # vite dev server

demos/wc26-intro is a single static page — just open demos/wc26-intro/index.html in your browser.

Want to see how it's done? Open ClawCodex in any empty directory and ask it to build something — they were all generated exactly that way.

🎓 Why ClawCodex?

Based on Real Source Code

Not a clone — Ported from actual TypeScript implementation
Architectural fidelity — Maintains proven design patterns
Improvements — Better error handling, more tests, cleaner code

Python Native

Type hints — Full type annotations
Modern Python — Uses 3.10+ features
Idiomatic — Clean, Pythonic code

User Focused

3-step setup — Clone, configure (clawcodex login), run (clawcodex)
Interactive config — Provider, base URL, and default model in one flow
Inline or TUI — Default terminal-native REPL; opt-in Textual UI
Scriptable — -p / JSON / NDJSON for automation
Session persistence — Save and reload conversations

Architecture

For the six core abstractions (query loop, tools, tasks, two-tier state, memory, hooks) and the golden path from user input to model output, see docs/ARCHITECTURE.md. It is the recommended starting point for new contributors.

The reference for the original Claude Code architecture is at claude-code-from-source/book/ch01-architecture.md; the chapter-by-chapter port gap analyses and refactoring plans live under my-docs/.

📦 Project Structure

clawcodex/
├── src/
│   ├── cli.py              # CLI entry (console: clawcodex)
│   ├── entrypoints/        # Headless (-p) and TUI bootstraps
│   ├── repl/               # Inline REPL (prompt_toolkit + Rich)
│   ├── tui/                # Textual UI (--tui, /tui)
│   ├── providers/          # Anthropic, OpenAI, GLM, Minimax, OpenRouter, DeepSeek
│   ├── agent/              # Conversation, session, prompts
│   ├── tool_system/        # Agent loop, tools, schemas
│   ├── skills/             # SKILL.md loading and skill tool
│   ├── services/           # MCP, compact, IDE bridge, tool execution, …
│   ├── context_system/     # Workspace / git / CLAUDE.md context
│   ├── permissions/        # Permission modes and bash parsing
│   ├── hooks/              # Hook types and execution helpers
│   └── command_system/     # Slash commands and substitution
├── typescript/             # Reference / parity source (not required to run Python CLI)
├── tests/                  # pytest suites
├── docs/                   # Guides, i18n READMEs, refactor notes
├── .clawcodex/skills/      # Project-local skills (optional)
├── FEATURE_LIST.md         # Capability matrix and roadmap
└── pyproject.toml          # Package metadata and clawcodex script

🤝 Contributing

We welcome contributions!

# Quick dev setup
pip install -e .[dev]
python -m pytest tests/ -v

See CONTRIBUTING.md for guidelines.

📖 Documentation

SETUP_GUIDE.md — Detailed installation
CONTRIBUTING.md — Development guide
TESTING.md — Testing guide
CHANGELOG.md — Version history

⚡ Performance

Startup: < 1 second
Memory: < 50MB
Response: Turn-based assistant output with Rich markdown rendering

🔒 Security

✅ Basic Local Safety Practices

No sensitive data in Git
API keys obfuscated in config
.env files ignored
Safe for local development workflows

📄 License

MIT License — See LICENSE

🙏 Acknowledgments

Based on Claude Code TypeScript source
Independent educational project
Not affiliated with Anthropic

🌟 Show Your Support

If you find this useful, please star ⭐ the repo!

Made with ❤️ by ClawCodex Team

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ClawCodex

🐋🔥 DeepSeek Prefix Cache

Run long agentic coding sessions for pennies

Cache-hit input bills at ~$0.0435 / 1M tokens — about 230× cheaper than Claude Fable 5 ($10 / 1M).

⚡ Quick Install

📰 News

🎯 Why ClawCodex?

🏆 SWE-bench Verified — clawcodex outperforms openclaude on the same model

⭐ Star History

✨ Features

Streaming Agent Experience

Programmable Skill Runtime

Multi-Provider Support

Interactive REPL (default) and Textual TUI (opt-in)

Complete CLI

📊 Status

Core Systems

Tool System (30+ Tools Implemented)

Roadmap Progress

🚀 Quick Start

Install

Configure

Option 1: Interactive (Recommended)

Run

💡 Usage

REPL Commands

Skills (Slash Commands)

🎨 Demos

🎓 Why ClawCodex?

Based on Real Source Code

Python Native

User Focused

Architecture

📦 Project Structure

🤝 Contributing

📖 Documentation

⚡ Performance

🔒 Security

📄 License

🙏 Acknowledgments

🌟 Show Your Support

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Cache-hit input bills at `~$0.0435` / 1M tokens — about 230× cheaper than Claude Fable 5 (`$10` / 1M).

🏆 SWE-bench Verified — `clawcodex` outperforms `openclaude` on the same model

Packages