claw-code-harness

安装量: 275
排名: #7401

安装

npx skills add https://github.com/aradotso/trending-skills --skill claw-code-harness

Claw Code Harness Skill by ara.so — Daily 2026 Skills collection. Claw Code is a clean-room Python (with Rust port in progress) rewrite of the Claude Code agent harness. It provides tooling to inspect the port manifest, enumerate subsystems, audit parity against an archived source, and query tool/command inventories — all via a CLI entrypoint and importable Python modules. Installation

Clone the repository

git clone https://github.com/instructkr/claw-code.git cd claw-code

Install dependencies (standard library only for core; extras for dev)

pip install -r requirements.txt

if present, else no external deps required

Verify the workspace

python3 -m unittest discover -s tests -v No PyPI package yet — use directly from source. Repository Layout . ├── src/ │ ├── init.py │ ├── commands.py # Python-side command port metadata │ ├── main.py # CLI entrypoint │ ├── models.py # Dataclasses: Subsystem, Module, BacklogState │ ├── port_manifest.py # Current Python workspace structure summary │ ├── query_engine.py # Renders porting summary from active workspace │ ├── task.py # Task primitives │ └── tools.py # Python-side tool port metadata └── tests/ # Unittest suite CLI Reference All commands are invoked via python3 -m src.main . summary Render the full Python porting summary. python3 -m src.main summary manifest Print the current Python workspace manifest (file surface + subsystem names). python3 -m src.main manifest subsystems List known subsystems, with optional limit. python3 -m src.main subsystems python3 -m src.main subsystems --limit 16 commands Inspect mirrored command inventory. python3 -m src.main commands python3 -m src.main commands --limit 10 tools Inspect mirrored tool inventory. python3 -m src.main tools python3 -m src.main tools --limit 10 parity-audit Run parity audit against a locally present (gitignored) archived snapshot. python3 -m src.main parity-audit Requires the local archive to be present at its expected path (not tracked in git). Core Modules & API src/models.py — Dataclasses from src . models import Subsystem , Module , BacklogState

A subsystem groups related modules

sub

Subsystem ( name = "tool-harness" , modules = [ ] , status = "in-progress" )

A module represents a single ported file

mod

Module ( name = "tools.py" , ported = True , notes = "tool metadata only" )

BacklogState tracks overall port progress

state

BacklogState
(
total_subsystems
=
8
,
ported
=
5
,
backlog
=
3
,
notes
=
"runtime slices pending"
)
src/tools.py
— Tool Port Metadata
from
src
.
tools
import
get_tools
,
ToolMeta
tools
:
list
[
ToolMeta
]
=
get_tools
(
)
for
t
in
tools
[
:
5
]
:
print
(
t
.
name
,
t
.
ported
,
t
.
description
)
src/commands.py
— Command Port Metadata
from
src
.
commands
import
get_commands
,
CommandMeta
commands
:
list
[
CommandMeta
]
=
get_commands
(
)
for
c
in
commands
[
:
5
]
:
print
(
c
.
name
,
c
.
ported
)
src/query_engine.py
— Porting Summary Renderer
from
src
.
query_engine
import
render_summary
summary_text
:
str
=
render_summary
(
)
print
(
summary_text
)
src/port_manifest.py
— Manifest Access
from
src
.
port_manifest
import
get_manifest
,
ManifestEntry
entries
:
list
[
ManifestEntry
]
=
get_manifest
(
)
for
entry
in
entries
:
print
(
entry
.
path
,
entry
.
status
)
Common Patterns
Pattern 1: Check how many tools are ported
from
src
.
tools
import
get_tools
tools
=
get_tools
(
)
ported
=
[
t
for
t
in
tools
if
t
.
ported
]
print
(
f"
{
len
(
ported
)
}
/
{
len
(
tools
)
}
tools ported"
)
Pattern 2: Find unported subsystems
from
src
.
port_manifest
import
get_manifest
backlog
=
[
e
for
e
in
get_manifest
(
)
if
e
.
status
!=
"ported"
]
for
entry
in
backlog
:
print
(
f"BACKLOG:
{
entry
.
path
}
"
)
Pattern 3: Programmatic summary pipeline
from
src
.
query_engine
import
render_summary
from
src
.
commands
import
get_commands
from
src
.
tools
import
get_tools
print
(
"=== Summary ==="
)
print
(
render_summary
(
)
)
print
(
"\n=== Commands ==="
)
for
c
in
get_commands
(
limit
=
5
)
:
print
(
f"
{
c
.
name
}
ported=
{
c
.
ported
}
"
)
print
(
"\n=== Tools ==="
)
for
t
in
get_tools
(
limit
=
5
)
:
print
(
f"
{
t
.
name
}
ported= { t . ported } " ) Pattern 4: Run tests before contributing python3 -m unittest discover -s tests -v Pattern 5: Using as part of an OmX/agent workflow

Generate summary artifact for an agent to consume

python3 -m src.main summary

/tmp/claw_summary.txt

Feed into another agent tool or diff against previous checkpoint

diff /tmp/claw_summary_prev.txt /tmp/claw_summary.txt Rust Port (In Progress) The Rust rewrite is on the dev/rust branch.

Switch to the Rust branch

git fetch origin dev/rust git checkout dev/rust

Build (requires Rust toolchain: https://rustup.rs)

cargo build

Run

cargo run -- summary The Rust port aims for a faster, memory-safe harness runtime. It is not yet merged into main. Until then, use the Python implementation for all production workflows. Troubleshooting Problem Cause Fix ModuleNotFoundError: No module named 'src' Running from wrong directory cd to repo root, then python3 -m src.main ... parity-audit exits with "archive not found" Local snapshot not present Place the archive at the expected local path (see port_manifest.py for the path constant) Tests fail with import errors Missing init.py Ensure src/init.py exists; re-clone if needed --limit flag not recognized Old checkout git pull origin main Rust build fails Toolchain not installed Run curl https://sh.rustup.rs -sSf | sh then retry Key Design Notes for AI Agents No external runtime dependencies for the core Python modules — safe to run in sandboxed environments. query_engine.py is the single aggregation point — prefer it over calling individual modules when you need a full picture. models.py dataclasses are the canonical data shapes; always import types from there, not inline dicts. parity-audit is read-only — it does not modify any tracked files. The project is not affiliated with Anthropic and contains no proprietary Claude Code source.

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