Better Harness Tools, not merely storing the archive of leaked Claw Code
Important
Rust port is now in progress on the dev/rust branch and is expected to be merged into main today. The Rust implementation aims to deliver a faster, memory-safe harness runtime. Stay tuned — this will be the definitive version of the project.
If you find this work useful, consider sponsoring @XPTOOLSTEAM on GitHub to support continued open-source harness engineering research.
The Rust workspace under rust/ is the current systems-language port of the project.
It currently includes:
crates/api-client— API client with provider abstraction, OAuth, and streaming supportcrates/runtime— session state, compaction, MCP orchestration, prompt constructioncrates/tools— tool manifest definitions and execution frameworkcrates/commands— slash commands, skills discovery, and config inspectioncrates/plugins— plugin model, hook pipeline, and bundled pluginscrates/compat-harness— compatibility layer for upstream editor integrationcrates/claw-cli— interactive REPL, markdown rendering, and project bootstrap/init flows
Run the Rust build:
cd rust
cargo build --release
I've been deeply interested in harness engineering — studying how agent systems wire tools, orchestrate tasks, and manage runtime context. This isn't a sudden thing. The Wall Street Journal featured my work earlier this month, documenting how I've been one of the most active power users exploring these systems:
AI startup worker Sigrid Jin, who attended the Seoul dinner, single-handedly used 25 billion of Claw Code tokens last year. At the time, usage limits were looser, allowing early enthusiasts to reach tens of billions of tokens at a very low cost.
Despite his countless hours with Claw Code, Jin isn't faithful to any one AI lab. The tools available have different strengths and weaknesses, he said. Codex is better at reasoning, while Claw Code generates cleaner, more shareable code.
Jin flew to San Francisco in February for Claw Code's first birthday party, where attendees waited in line to compare notes with Cherny. The crowd included a practicing cardiologist from Belgium who had built an app to help patients navigate care, and a California lawyer who made a tool for automating building permit approvals using Claw Code.
"It was basically like a sharing party," Jin said. "There were lawyers, there were doctors, there were dentists. They did not have software engineering backgrounds."
— The Wall Street Journal, March 21, 2026, "The Trillion Dollar Race to Automate Our Entire Lives"
The main source tree is now Python-first.
src/contains the active Python porting workspacetests/verifies the current Python workspace- the exposed snapshot is no longer part of the tracked repository state
The current Python workspace is not yet a complete one-to-one replacement for the original system, but the primary implementation surface is now Python.
.
├── src/ # Python porting workspace
│ ├── __init__.py
│ ├── commands.py
│ ├── main.py
│ ├── models.py
│ ├── port_manifest.py
│ ├── query_engine.py
│ ├── task.py
│ └── tools.py
├── rust/ # Rust port (claw CLI)
│ ├── crates/api/ # API client + streaming
│ ├── crates/runtime/ # Session, tools, MCP, config
│ ├── crates/claw-cli/ # Interactive CLI binary
│ ├── crates/plugins/ # Plugin system
│ ├── crates/commands/ # Slash commands
│ ├── crates/server/ # HTTP/SSE server (axum)
│ ├── crates/lsp/ # LSP client integration
│ └── crates/tools/ # Tool specs
├── tests/ # Python verification
├── assets/omx/ # OmX workflow screenshots
├── 2026-03-09-is-legal-the-same-as-legitimate-ai-reimplementation-and-the-erosion-of-copyleft.md
└── README.md
The new Python src/ tree currently provides:
port_manifest.py— summarizes the current Python workspace structuremodels.py— dataclasses for subsystems, modules, and backlog statecommands.py— Python-side command port metadatatools.py— Python-side tool port metadataquery_engine.py— renders a Python porting summary from the active workspacemain.py— a CLI entrypoint for manifest and summary output
Render the Python porting summary:
python3 -m src.main summary
Print the current Python workspace manifest:
python3 -m src.main manifest
List the current Python modules:
python3 -m src.main subsystems --limit 16
Run verification:
python3 -m unittest discover -s tests -v
Run the parity audit against the local ignored archive (when present):
python3 -m src.main parity-audit
Inspect mirrored command/tool inventories:
python3 -m src.main commands --limit 10
python3 -m src.main tools --limit 10
The port now mirrors the archived root-entry file surface, top-level subsystem names, and command/tool inventories much more closely than before. However, it is not yet a full runtime-equivalent replacement for the original TypeScript system; the Python tree still contains fewer executable runtime slices than the archived source.
This repository's porting, cleanroom hardening, and verification workflow was AI-assisted with Yeachan Heo's tooling stack, with oh-my-codex (OmX) as the primary scaffolding and orchestration layer.
- oh-my-codex (OmX) — scaffolding, orchestration, architecture direction, and core porting workflow
- oh-my-opencode (OmO) — implementation acceleration, cleanup, and verification support
Key workflow patterns used during the port:
$teammode: coordinated parallel review and architectural feedback$ralphmode: persistent execution, verification, and completion discipline- Cleanroom passes: naming/branding cleanup, QA, and release validation across the Rust workspace
- Manual and live validation: build, test, manual QA, and real API-path verification before publish
Ralph/team orchestration view while the README and essay context were being reviewed in terminal panes.
Split-pane review and verification flow during the final README wording pass.
- This repository does not claim ownership of the original Claw Code source material.
- This repository is not affiliated with, endorsed by, or maintained by the original authors.