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/askwigconsulting/cohort/ratchetgit clone --depth 1 https://github.com/askwigconsulting/cohortWrote 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/askwigconsulting/cohort/ratchet)<a href="https://agentmods.dev/commands/askwigconsulting/cohort/ratchet"><img src="https://agentmods.dev/badge/commands/askwigconsulting/cohort/ratchet.svg" alt="Measured on agentmods" 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 | $0.00033 | $0.00828 |
| Opus 5 | $0.00016 | $0.00414 |
| Sonnet 5 | $0.00007 | $0.00166 |
| Haiku 4.5 | $0.00003 | $0.00083 |
Grade A, and why
ratchet 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 3d 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 — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Point it at a number and let it climb. /ratchet is a metric-gated optimization loop —
Karpathy's AutoResearch pattern (propose a change, run a fixed-budget evaluator, keep the
commit if the metric improved, git reset if not, repeat) adapted to Cohort's human gate:
the whole climb runs inside a throwaway git worktree, bounded by a budget, and you
review the staircase and merge via PR. The autonomy is the inner loop; the merge stays
gated. Reach for it when the win is measurable and the search is tedious — a perf number, a
benchmark score, a failing-test count, a lint count.
Runs on a coordinator tier (Fable or Opus): you set up the contract and read the staircase; the loop does the methodical climbing.
The three-part contract
Make these three things explicit before you start — it is what makes autonomy safe:
- The immutable evaluator — one command that prints the objective number, and that the
loop never edits. This is the ground truth (Karpathy's
prepare.py). If the doer could change the evaluator, it could optimize the metric by lying; it can't, because it only ever touches the worktree's tracked code, which you review. - The sandbox — a detached worktree off HEAD. Every proposal lands only here; your working tree is never touched, and a bad run is thrown away.
- The direction — the objective in words. Keep it tight and surgical ("lower p99
latency in
handler.py; change nothing else").
Run it
cohort engine ratchet gpt \
--evaluator "pytest tests/bench.py -q 2>&1 | tail -1" \
--metric-regex 'score=([0-9.]+)' \
--goal maximize --budget 15 --footprint src/handler.py
gpt(Codex, edits under its own sandbox) orgrok(egress-gated agentic patch) does the proposing; the loop's keep/revert, worktree, ledger, and budget are enforced in code.- Each iteration is fed the current best and the recent ledger so it calibrates what to try
next — the
ratchet-results.tsvstaircase is the loop's memory. - Ties and non-improvements revert. The lineage only advances on a real gain.
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.
- 3d ago First seen · 69 lines · 33 tokens per session scan A 8a91d42d2735
ratchet is a command published in the GitHub repository askwigconsulting/cohort (2 stars, last pushed 26d ago), licensed MIT. It adds 33 tokens to every session and 828 once invoked, about $0.0002 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.
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.