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/roomi-fields/paper-trailWrote 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/roomi-fields/paper-trail/paper-trail-resolve-textbooks)<a href="https://agentmods.dev/commands/roomi-fields/paper-trail/paper-trail-resolve-textbooks"><img src="https://agentmods.dev/badge/commands/roomi-fields/paper-trail/paper-trail-resolve-textbooks/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/roomi-fields/paper-trail/paper-trail-resolve-textbooks"><img src="https://agentmods.dev/badge/commands/roomi-fields/paper-trail/paper-trail-resolve-textbooks.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 | $0.00062 | $0.00660 |
| Opus 5 | $0.00031 | $0.00330 |
| Sonnet 5 | $0.00012 | $0.00132 |
| Haiku 4.5 | $0.00006 | $0.00066 |
Grade A, and why
paper-trail-resolve-textbooks 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 11d 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 — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/paper-trail:resolve-textbooks — Automated IA pass on incomplete refs
Nettoie les refs ingérées avec year/title manquant. Process 100% automatisé, pas de décision humaine ad-hoc.
Usage
/paper-trail:resolve-textbooks # dry-run : montre les décisions
/paper-trail:resolve-textbooks --apply # applique
Ce que fait Claude (workflow strict)
-
Liste les candidates :
python3 -m pipeline resolve-textbooks --list > /tmp/textbook_candidates.jsonLe JSON contient : slug, author, year, title, state, ingest_source, pdf_path, et
siblings(autres refs du registre avec même lastname, pour aider à la fusion). -
Invoque le sub-agent
textbook-resolveravec le JSON en input :Agent(subagent_type="textbook-resolver", prompt="<contenu de /tmp/textbook_candidates.json>")Le sub-agent applique les règles définies dans son contrat (cf.
agents/textbook-resolver.md) :- Préfère
merge_intosi un sibling avec PDF correspond - Sinon
completesi textbook canonique reconnu (Sipser, Carton, etc.) - Sinon
blocked(humain tranche)
- Préfère
-
Sauve le JSON de décisions retourné par le sub-agent dans
/tmp/textbook_decisions.json. -
Mode dry-run (par défaut) : affiche le résumé des décisions (nb par action), demande confirmation avant
--apply. -
Mode
--apply:python3 -m pipeline resolve-textbooks \ --apply-from /tmp/textbook_decisions.json -
Récap final : N merged, N completed, N blocked.
Garde-fous
- Sub-agent ne fabrique JAMAIS une année ou un titre incertain.
Confidence < 80% →
blocked(l'utilisateur tranchera via/paper-trail:decide <slug>). - Fusions traçables : la ref source passe en
retractedavecretracted_reason: merged_into:<target>. Réversible via git. - Pas de bricolage manuel : Claude ne construit pas les décisions lui-même, il délègue au sub-agent. Process reproductible.
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.
- 11d ago First seen · 68 lines · 62 tokens per session scan A b16d92f5650c
paper-trail-resolve-textbooks is a command published in the GitHub repository roomi-fields/paper-trail (5 stars, last pushed 7d ago), licensed MIT. It adds 62 tokens to every session and 660 once invoked, about $0.0003 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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