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.
git clone --depth 1 https://github.com/rhan1/crewlineWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/rhan1/crewline/burn)<a href="https://agentmods.dev/commands/rhan1/crewline/burn"><img src="https://agentmods.dev/badge/commands/rhan1/crewline/burn/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/rhan1/crewline/burn"><img src="https://agentmods.dev/badge/commands/rhan1/crewline/burn.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00024 | $0.00346 |
| Opus 5.5 | $0.00010 | $0.00138 |
| Sonnet 5.5 | $0.00005 | $0.00069 |
| Haiku 4.5 | $0.00002 | $0.00035 |
Grade A, and why
burn 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 2mo 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
Run this and report the result verbatim, then add one line of interpretation:
node $HOME/.claude/hooks/burn-rate-advisor.js --report
Interpretation guide:
- SPRINT — the window resets soon and a large share of the budget is still unspent. That budget is forfeited at reset, so spend it: fan out to the widest useful set of parallel workers now (multiple Agent calls in ONE message so they run concurrently, or a Workflow), route mechanical work to your external CLI executors (Codex/Gemini) so it costs no Claude budget, and prefer breadth over depth. Work still running at reset continues into a fresh window.
- SPEND — ahead of pace. Parallelize freely; don't serialize what could fan out.
- NORMAL — on pace. No change in posture.
- CONSERVE — burning faster than the clock. Sequential work, 2–3 workers max on the cheapest sufficient tier, checkpoint for resume.
- CRITICAL — near the wall. Finish and checkpoint the current item, no new
fan-outs, chain the rest to the next window (
/execute-at-reset).
If a 7d note is attached, it wins: the weekly window does not refill today, so a 5h surplus is not free when 7d is high.
If the report says the signal is stale, the statusline hasn't rendered recently — trust the live statusline numbers instead.
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.
- 2mo ago First seen · 31 lines · 24 tokens per session scan A 14fc87b9ee20
burn is a command published in the GitHub repository rhan1/crewline (2 stars, last pushed 11d ago), licensed MIT. It adds 24 tokens to every session and 346 once invoked, about $0.0001 per session on Opus 5.5. 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
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.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
speckit.bug.fix
Apply the remediation from a bug assessment and record what was changed.