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/Marazii/research-co-pilotWrote 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/marazii/research-co-pilot/respond)<a href="https://agentmods.dev/commands/marazii/research-co-pilot/respond"><img src="https://agentmods.dev/badge/commands/marazii/research-co-pilot/respond.svg" alt="Measured on agentmods" 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 | $0.00028 | $0.00376 |
| Opus 5 | $0.00014 | $0.00188 |
| Sonnet 5 | $0.00006 | $0.00075 |
| Haiku 4.5 | $0.00003 | $0.00038 |
Grade A, and why
respond 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 7d 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
Invoke the reviewer-response skill from the research-co-pilot plugin and execute its full workflow.
The skill file is at skills/reviewer-response/SKILL.md relative to this plugin. Read it and follow it precisely — including:
- Phase 1: Intake (reviewer comments, manuscript, round number, journal, posture).
- Phase 2: Categorize every comment (concession + revision / partial concession / polite pushback / clarification / out of scope / minor).
- Phase 3: Draft response per comment with verbatim reviewer quote, substantive response, and revision pointer.
- Phase 4: Draft prose revisions (delegate to
manuscript-drafterfor anything > one paragraph to preserve voice). - Phase 5: Cover letter to editor (under one page; surface pushback up front).
- Phase 6: Assemble package —
response_to_reviewers_<round>/directory with cover letter, response, revised manuscript, tracked-changes version if needed, change log. - Phase 7: Self-audit — every comment addressed; every claimed revision actually present; tone polite throughout; voice matches existing manuscript.
Address every reviewer point. Never concede a point the data doesn't support. Be unfailingly polite even when pushing back.
User input: $ARGUMENTS
If no inputs were given, ask for: path to reviewer comments (one file or multiple), path to the manuscript, round number (R1 / R2 / R3), journal name, and (if R2 or later) the path to the prior response letter.
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.
- 7d ago First seen · 23 lines · 28 tokens per session scan A 4b16aeba5731
respond is a command published in the GitHub repository Marazii/research-co-pilot (13 stars, last pushed 3mo ago), licensed MIT. It adds 28 tokens to every session and 376 once invoked, about $0.0001 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).
srs-sm
Draft and QC the Supplementary Materials: scope approval → SM writing → figure QC for SM figures.
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.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.