Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/ychampion/codeclaw/docsnpx skills add ychampion/codeclaw --skill docsgit clone --depth 1 https://github.com/ychampion/codeclawWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00054 | $0.01675 |
| Opus 5 | $0.00027 | $0.00838 |
| Sonnet 5 | $0.00011 | $0.00335 |
| Haiku 4.5 | $0.00005 | $0.00168 |
Grade A, and why
codeclaw scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
codeclaw Skill
THE RULE
Every codeclaw command outputs next_steps. FOLLOW THEM.
Do not memorize the flow. Do not skip steps. Do not improvise.
Run the command -> read the output -> follow next_steps. That's it.
The CLI tracks your stage (1-4: auth -> configure -> review -> done).
codeclaw export (push) is gated -- you must run codeclaw confirm first or it will refuse.
Getting Started
Run codeclaw status (or codeclaw prep for full details) and follow the next_steps.
Output Format
codeclaw prep,codeclaw config,codeclaw status, andcodeclaw confirmoutput pure JSONcodeclaw exportoutputs human-readable text followed by---CODECLAW_JSON---and a JSON block- Always parse the JSON and act on
next_steps
Key fields:
stage/stage_number/total_stages-- where you arenext_steps-- follow these in ordernext_command-- the single most important command to run next (null if user input needed first)
PII Audit (Stage 3)
After codeclaw export --no-push, follow the next_steps in the JSON output. The flow is:
- Ask the user their full name -- then grep the export for it
- Run the pii_commands from the JSON output and review results with the user
- Ask the user what else to look for -- company names, client names, private URLs, other people's names, custom domains
- Deep manual scan -- sample ~20 sessions (beginning, middle, end) and look for anything sensitive the regex missed
- Fix and re-export if anything found:
codeclaw config --redact "string"thencodeclaw export --no-push - Run
codeclaw confirmwith text attestations -- pass--full-name,--attest-full-name,--attest-sensitive, and--attest-manual-scan. It runs PII scan, verifies attestations, shows project breakdown, and unlocks pushing. - Push only after explicit user confirmation:
codeclaw export --publish-attestation "User explicitly approved publishing to Hugging Face."
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 115 lines · 54 tokens per session scan A 3374ffc25a61
codeclaw is a skill published in the GitHub repository ychampion/codeclaw (11 stars, last pushed 6mo ago), licensed MIT. It adds 54 tokens to every session and 1,675 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
trulens-dataset-curation
Create and curate evaluation datasets with ground truth for TruLens.
portaljs-add-dataset
Add a dataset (CSV, TSV, JSON, or GeoJSON) to an existing PortalJS portal. Appends an entry to datasets.json so the catalog and showcase render it automatically; routes the data by source (local file vs remote URL) — R2 via Git LFS by default, remote URLs by passthrough. Use when registering a new dataset in a…
digital-health-clinical-asr-build
Stage 2 of the Clinical ASR Flywheel. Use when curating clinical terms, tagging IPA, and synthesizing a NeMo manifest. NOT for scoring (use /digital-health-clinical-asr-eval).
tao-convert-dataset-format
Run tao-daft convert to convert NVIDIA TAO DAFT datasets between supported formats. Do not use for non-DAFT data. Use when the user asks to convert a DAFT dataset, change DAFT format, change a TAO dataset format, or run tao-daft convert.
tao-validate-dataset-format
Run tao-daft validate to check NVIDIA TAO DAFT datasets for structure, schema, and cross-reference errors. Do not use for non-DAFT formats. Use when the user asks to validate a DAFT dataset, check DAFT schema, validate a TAO dataset format, or run tao-daft validate.
opencaselaw-maintenance
Use for OpenCaseLaw autonomous maintenance loops, production health checks, scraper/completeness triage, safe deploy decisions, and Codex automation work in this repo. Do not use for ordinary feature work unless the task is about operational safety, corpus completeness, or maintenance automation.