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 commands/rohitbind123/claude-setup/clawgit clone --depth 1 https://github.com/RohitBind123/claude-setupWhat 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 | $0.00023 | $0.00464 |
| Opus 5 | $0.00012 | $0.00232 |
| Sonnet 5 | $0.00005 | $0.00093 |
| Haiku 4.5 | $0.00002 | $0.00046 |
Grade A, and why
claw 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.
What it actually says
Claw Command
Start an interactive AI agent session that persists conversation history to disk and optionally loads ECC skill context.
Usage
node scripts/claw.js
Or via npm:
npm run claw
Environment Variables
| Variable | Default | Description |
|---|---|---|
CLAW_SESSION |
default |
Session name (alphanumeric + hyphens) |
CLAW_SKILLS |
(empty) | Comma-separated skill names to load as system context |
REPL Commands
Inside the REPL, type these commands directly at the prompt:
/clear Clear current session history
/history Print full conversation history
/sessions List all saved sessions
/help Show available commands
exit Quit the REPL
How It Works
- Reads
CLAW_SESSIONenv var to select a named session (default:default) - Loads conversation history from
~/.claude/claw/{session}.md - Optionally loads ECC skill context from
CLAW_SKILLSenv var - Enters a blocking prompt loop — each user message is sent to
claude -pwith full history - Responses are appended to the session file for persistence across restarts
Session Storage
Sessions are stored as Markdown files in ~/.claude/claw/:
~/.claude/claw/default.md
~/.claude/claw/my-project.md
Each turn is formatted as:
### [2025-01-15T10:30:00.000Z] User
What does this function do?
---
### [2025-01-15T10:30:05.000Z] Assistant
This function calculates...
---
Examples
# Start default session
node scripts/claw.js
# Named session
CLAW_SESSION=my-project node scripts/claw.js
# With skill context
CLAW_SKILLS=tdd-workflow,security-review node scripts/claw.js
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 · 80 lines · 23 tokens per session scan A 8a6f9dce1b10
claw is a command published in the GitHub repository RohitBind123/claude-setup (2 stars, last pushed 4mo ago), licensed MIT. It adds 23 tokens to every session and 464 once invoked, about $0.0001 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 2026-08-31.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
constitution
Create or update the project constitution from interactive or provided principle inputs.