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/respond-reviewers)<a href="https://agentmods.dev/commands/tobiasblask/open-paper-machine/respond-reviewers"><img src="https://agentmods.dev/badge/commands/tobiasblask/open-paper-machine/respond-reviewers/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/respond-reviewers"><img src="https://agentmods.dev/badge/commands/tobiasblask/open-paper-machine/respond-reviewers.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 | $0.00055 | $0.00348 |
| Opus 5 | $0.00028 | $0.00174 |
| Sonnet 5 | $0.00011 | $0.00070 |
| Haiku 4.5 | $0.00006 | $0.00035 |
Grade A, and why
respond-reviewers 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 12d 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
Respond to Reviewers: $ARGUMENTS
Read the review-engine skill at skills/review-engine/SKILL.md and execute the full
7-step workflow:
- EXTRACT review points from the provided input
- MAP each point to its location in
paper.tex - CLASSIFY action type and priority for each point
- PLAN and present the change plan for user approval (quality gate)
- IMPLEMENT approved changes in dependency order
- VERIFY by recompiling LaTeX and generating latexdiff
- DOCUMENT with change log, revision letter, and orchestration log entry
Input
$ARGUMENTS can be:
- File path to an annotated PDF (e.g.,
@review_r1.pdf) - Pasted reviewer comments from a journal decision letter
- "round N" to continue a numbered revision series
- Self-review output from Phase 6
Output
- Updated
paper.texwith all approved changes implemented - Recompiled
paper.pdf(0 errors) paper_diff.pdfwith visual change tracking (latexdiff)outputs/revision_log_rN.mdwith detailed change log- Optional:
outputs/revision_letter.mdfor journal R&R responses
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.
- 12d ago First seen · 37 lines · 55 tokens per session scan A cc666089d846
respond-reviewers is a command published in the GitHub repository TobiasBlask/open-paper-machine (18 stars, last pushed 5mo ago), licensed MIT. It adds 55 tokens to every session and 348 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 2026-08-30.
Other commands, from other repositories
openehr-explain
One-stop router that explains or looks up any openEHR thing — auto-detects an archetype, a template, an RM/AM/BASE type, an RM structural concept, an ADL idiom, an AQL query or keyword, or a terminology code (replaces /archetype-explain, /template-explain, /type-spec, /rm-structure, /adl-idiom, /terminology).
create-scene
Create a single animated scene for mathematical visualization.
ars-lit-review
ARS academic-paper lit-review mode — annotated bibliography in paper format.
ars-citation-check
ARS academic-paper citation-check mode — citation error report.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.