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/aiosai/aipass/compassgit clone --depth 1 https://github.com/AIOSAI/AIPassWhat 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 | $0.00000 | $0.00508 |
| Opus 5 | $0.00000 | $0.00254 |
| Sonnet 5 | $0.00000 | $0.00102 |
| Haiku 4.5 | $0.00000 | $0.00051 |
Grade A, and why
compass 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 — 36 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Compass — Record a Decision
Purpose: Capture the decision just made into compass (the rated decision engine) with the user's rating and note. The user fires this when they notice a decision worth recording — they supply the judgement, you supply the decision text from the conversation. This is the human-triggered answer to the "noticing" problem: the user notices, you describe and store.
Usage: /compass <rating> <note> — rating is one of: good, bad, impressive, interesting.
Examples:
/compass good chose to continue the dead agent instead of starting fresh/compass bad reached into the branch instead of dispatching/compass impressive(rating only — you write context, decision, and note from the conversation)
Arguments: $ARGUMENTS
Execution
- Parse
$ARGUMENTS:- First token =
rating. It MUST be one ofgood | bad | impressive | interesting. If it isn't, don't guess — ask the user which rating they meant and stop. - Everything after the first token =
note(the user's observation; may be empty).
- First token =
- From the recent conversation, identify the decision being rated. Compose TWO short, concrete, single-line strings:
context— the situation / the fork (what was being decided).decision— what was actually chosen. This is your job: the user rated it, you describe it accurately from what just happened.
- Store it (source is
user, since they triggered the rating):
Omitdrone @devpulse compass add "<context>" "<decision>" --rating <rating> --note "<note>" --source user--noteif the note is empty. - Confirm in one line: the rating, the decision recorded, and the new id.
Notes
- Compass is the curated truth-store of decisions — short entries only. Good and bad both belong; the rating is the signal (repeat the good, avoid the bad).
- Compass is separate from @memory. Do NOT also write this to
.trinity/or memory — different store, different purpose. - If the decision the user means is ambiguous, ask before storing. One good entry beats a vague one.
- Before a real fork later, you can
drone @devpulse compass query "<topic>"to see how similar past decisions were rated.
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 · 36 lines · 0 tokens per session scan A 446233704fd4
compass is a command published in the GitHub repository AIOSAI/AIPass (264 stars, last pushed 4d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 508 tokens. 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.
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