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/promptwheel-ai/logbook/pluginnpx skills add promptwheel-ai/logbook --skill plugingit clone --depth 1 https://github.com/promptwheel-ai/logbookWhat 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 | $0.00078 | $0.01184 |
| Opus 5 | $0.00039 | $0.00592 |
| Sonnet 5 | $0.00016 | $0.00237 |
| Haiku 4.5 | $0.00008 | $0.00118 |
Grade A, and why
logbook 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.
How it starts
The opening of the file, as written. The whole thing — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Logbook
npx @promptwheel/logbook # analyze current repo → 3 files
npx @promptwheel/logbook journey # the story, in color (writes nothing)
npx @promptwheel/logbook doctor # read-only artifact/wiring/query health
npx @promptwheel/logbook --json # events to stdout (writes nothing)
Never touches source or git history; writes only its own brief files. -n N caps commits; --since/--until for era scoping.
After running:
- Read
$(git rev-parse --show-toplevel)/LOGBOOK.mdcompletely before any history query. Do not replace this step with a broad keyword search. - Relay "What a fresh session should know" plus the 2-3 most notable findings. If Historical signal is LOW, use it only as a hotspot map; otherwise inspect task-relevant do-not-retry entries and fragile areas.
- TRIAGE, don't parrot: the logbook is the recall layer; you are the precision
layer. Cross-reference leads against the current task and verify any claim
you act on with
git show <sha>. Confirm it still applies at HEAD.
Findings are leads, not verdicts — a suppression event means "a human should
look here," not misconduct. If the repo is shallow, offer
git fetch --unshallow first.
If the artifacts, wiring, or query path look stale or inconsistent, run
npx -y @promptwheel/logbook@latest doctor and report its compact output.
Doctor is diagnostic and read-only; do not treat it as a refresh.
Investigation mode (when the user asks to dig into findings)
For each Notable event or flagged lead worth pursuing: git show <sha> the
commit, read the actual diff, and classify it — real weakening / sanctioned
maintenance / classifier artifact — with one line of evidence each. Check
whether flagged suppressions are STILL in the current tree (grep HEAD for
the skip/ignore near the flagged location). Present the triage as YOUR
judgment layered on the deterministic record — never edit the logbook files
to match your conclusions; the record and the reading stay separate.
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 · 102 lines · 78 tokens per session scan A 507165fe765c
logbook is a skill published in the GitHub repository promptwheel-ai/logbook (3 stars, last pushed 1mo ago), licensed MIT. It adds 78 tokens to every session and 1,184 once invoked, about $0.0004 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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