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/megaprompting/torque-loop/mapnpx skills add Megaprompting/torque-loop --skill mapgit clone --depth 1 https://github.com/Megaprompting/torque-loopWhat 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 | $0.00163 | $0.02489 |
| Opus 5 | $0.00081 | $0.01244 |
| Sonnet 5 | $0.00033 | $0.00498 |
| Haiku 4.5 | $0.00016 | $0.00249 |
Grade A, and why
map 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 yesterday.
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 — 188 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/ratchet:map — the fog-of-war gate
When uncertainty is high, the expensive mistake is a confident build in the wrong
direction. /ratchet:lock says: infer the missing value, name the assumption, move. That
is correct for low-uncertainty work. This command is its counterweight for the
high-uncertainty case — it maps the terrain before the build, so a wrong assumption is a
one-line correction on paper instead of a rewrite three PRs deep. What you deliver is the
map, not a build. You do not write code until it is handed over.
Method grafted from the
explore-unknownsskill; expressed in ratchet's own vocabulary — general mechanism, own words, backed by ratchet state. (Same graft discipline as the aperture dial.)
Two moves make the walk work:
- Show, don't ask. Never make the user describe intent from a blank page. Put something concrete in front of them — a sample, a throwaway mock, a few competing directions — and let them point at it. Recognition is cheap; invention is expensive.
- Pre-draft their reply. Close each turn with lettered options answerable in a few characters, so the user reacts instead of composing.
Step 0 — Load state, then scan the terrain
ratchet status
ratchet snapshot repo
Scan first. Gather what already exists, what is half-built, and what was tried and reverted — before you open your mouth. Serial questions on unread terrain waste the user's attention.
Procedure
Walk the four quadrants in order, naming the current one. Disclose material findings the moment you hit them; never close a quadrant off-screen.
-
Known knowns — settle the ground. State the facts, each cited to
file:line. Mark every assumption separately and say you will treat it as true until corrected, so a wrong premise gets caught now instead of after the build. -
Known unknowns — one question at a time. Ask the single highest-blast-radius question first (the answer that reshapes the most), not a wall of them. Give lettered options with a recommended answer. Close each question exactly one way, in front of the user: user answer, territory (you researched it, then show question + finding), probe (only touching the repo can answer it — commission a probe card, below), or OPEN (deferred, with what would unblock it and the route that will close it: ask-user, probe, park with owner+reason, promote to an assumption with a kill test, or a defect).
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.
- yesterday First seen · 188 lines · 163 tokens per session scan A fcd5f019f0a4
map is a skill published in the GitHub repository Megaprompting/torque-loop (5 stars, last pushed 1mo ago), licensed MIT. It adds 163 tokens to every session and 2,489 once invoked, about $0.0008 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.
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