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 skills add pedrohcgs/Claude-Mini --skill respond-to-refereesgit clone --depth 1 https://github.com/pedrohcgs/Claude-MiniWrote 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/skills/pedrohcgs/claude-mini/respond-to-referees)<a href="https://agentmods.dev/skills/pedrohcgs/claude-mini/respond-to-referees"><img src="https://agentmods.dev/badge/skills/pedrohcgs/claude-mini/respond-to-referees/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/skills/pedrohcgs/claude-mini/respond-to-referees"><img src="https://agentmods.dev/badge/skills/pedrohcgs/claude-mini/respond-to-referees.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 | $0.00070 | $0.02118 |
| Opus 5 | $0.00035 | $0.01059 |
| Sonnet 5 | $0.00014 | $0.00424 |
| Haiku 4.5 | $0.00007 | $0.00212 |
Grade A, and why
respond-to-referees 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.
This is a copy
97% identical to respond-to-referees — 6 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Respond to Referees
Produce a complete response-to-referees document by cross-referencing the referee report against the revised manuscript. Classify every concern, draft a courteous response for each, and flag anything unaddressed before submission.
Inputs
$0— path to the referee report$1— path to the revised manuscript
Supported formats and how to read them. In the commands below, FILE stands for the input path being converted — either $0 (referee report) or $1 (revised manuscript). Always use mktemp for the temp file (not a predictable /tmp/... name) so paths with spaces and concurrent runs don't collide, and so untrusted FILE paths can't clobber other temp files via symlink races.
| Format | How to extract text |
|---|---|
.tex, .qmd, .md, .txt |
Read directly with the Read tool. |
.pdf |
TMP=$(mktemp --suffix=.txt) && pdftotext "FILE" "$TMP" (poppler-utils; use mktemp -t ... on macOS if --suffix is unsupported). Grep "$TMP". |
.docx |
TMP=$(mktemp --suffix=.txt) && pandoc "FILE" -t plain -o "$TMP" (or docx2txt "FILE" "$TMP"). Grep "$TMP". |
.html |
TMP=$(mktemp --suffix=.txt) && pandoc "FILE" -t plain -o "$TMP". Grep "$TMP". |
If a required tool is missing or extraction fails, ask the user to provide a plain-text version (.txt or .md) and stop.
Workflow
Step 0: Convert Inputs to Plain Text
Before any parsing or grep, convert non-text inputs (.pdf, .docx, .html) to plain text using the table above. Keep both the temp text file (for grep) and the original (for citation page references).
Step 1: Parse the Referee Report
- Read the report end-to-end.
- Decompose into discrete numbered concerns. Common patterns:
- Numbered or bulleted enumerations ("1.", "(a)", "Comment 1", etc.).
- Section headers ("Major comments", "Minor comments").
- Implicit concerns embedded in prose paragraphs — extract these too.
- For each concern, capture:
- Concern ID (R{n}.{m} = referee n, comment m)
- Severity the referee assigned (major / minor / typographic)
- Verbatim quote of the most representative sentence (~25 words max)
- One-line summary in your own words
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 · 145 lines · 70 tokens per session scan A 72fc31572fdf
respond-to-referees is a skill published in the GitHub repository pedrohcgs/Claude-Mini (11 stars, last pushed 4mo ago), licensed MIT. It adds 70 tokens to every session and 2,118 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 97% identical to respond-to-referees, differing in 6 lines, and is treated as a copy.
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