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/TobiasBlask/open-paper-machineWrote 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/tobiasblask/open-paper-machine/monitor-literature)<a href="https://agentmods.dev/commands/tobiasblask/open-paper-machine/monitor-literature"><img src="https://agentmods.dev/badge/commands/tobiasblask/open-paper-machine/monitor-literature/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/tobiasblask/open-paper-machine/monitor-literature"><img src="https://agentmods.dev/badge/commands/tobiasblask/open-paper-machine/monitor-literature.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 | $0.00036 | $0.00299 |
| Opus 5 | $0.00018 | $0.00150 |
| Sonnet 5 | $0.00007 | $0.00060 |
| Haiku 4.5 | $0.00004 | $0.00030 |
Grade A, and why
monitor-literature 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 9d 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.
What it actually says
Monitor Literature: $ARGUMENTS
Activate the literature-engine skill. Read skills/literature-engine/SKILL.md in full.
Execute a monitoring search:
- LOAD the original search queries from
literature_base.csvmetadata orframing.md - RE-RUN all queries with
date_fromset to the last search date - DEDUPLICATE against existing
literature_base.csv - PRESENT only NEW papers not in the current literature base
- OFFER to add relevant new papers to
literature_base.csvandreferences.bib
Input
$ARGUMENTS can be:
- Empty — re-runs all original queries, shows papers since last search
- Specific query (e.g.,
"generative AI agents 2025") — runs a targeted update search - "since YYYY-MM-DD" — overrides the date filter
Output
- Summary of newly found papers (count, titles, venues)
- Updated
literature_base.csv(if user approves additions) - Updated
references.bib(if user approves additions)
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.
- 9d ago First seen · 32 lines · 36 tokens per session scan A f3d522f4295f
monitor-literature is a command published in the GitHub repository TobiasBlask/open-paper-machine (18 stars, last pushed 5mo ago), licensed MIT. It adds 36 tokens to every session and 299 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 2026-08-30.
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