Borrowing it
Nothing to install: this file belongs to Alexander-M-Dickerson/ai-asset-pricing. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Alexander-M-Dickerson/ai-asset-pricing/main/.claude/skills/respond-to-referee/SKILL.mdgit clone --depth 1 https://github.com/Alexander-M-Dickerson/ai-asset-pricingWrote 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/alexander-m-dickerson/ai-asset-pricing/respond-to-referee)<a href="https://agentmods.dev/skills/alexander-m-dickerson/ai-asset-pricing/respond-to-referee"><img src="https://agentmods.dev/badge/skills/alexander-m-dickerson/ai-asset-pricing/respond-to-referee/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/alexander-m-dickerson/ai-asset-pricing/respond-to-referee"><img src="https://agentmods.dev/badge/skills/alexander-m-dickerson/ai-asset-pricing/respond-to-referee.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 | $0.00024 | $0.01728 |
| Opus 5 | $0.00012 | $0.00864 |
| Sonnet 5 | $0.00005 | $0.00346 |
| Haiku 4.5 | $0.00002 | $0.00173 |
Grade A, and why
respond-to-referee 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.
How it starts
The opening of the file, as written. The whole thing — 201 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Respond to Referee Skill
Structured workflow for addressing referee comments. Operates in two modes:
- Single-point mode: Draft a response paragraph + LaTeX edits for one referee point
- Full-reply mode: Generate a complete standalone reply LaTeX document
Examples
/respond-to-referee referee2.md point 3-- address a specific point from a referee file/respond-to-referee referee2.md-- generate complete reply to all points in the file/respond-to-referee identification-- address a point by topic keyword
Input
The user provides:
- A referee report file (markdown or text)
- Either a specific point number, a topic keyword, or no argument (full reply)
Core Principles
These principles, distilled from journal editor guidelines and published advice (Noble 2017, PLOS Comp Bio; Review of Finance "Tips for Authors"), govern all referee responses.
Tone
- Grateful but not obsequious: "We thank the referee for this suggestion" (good) vs. "We are deeply grateful for this invaluable insight" (too much)
- Accept blame for misunderstandings: If the referee misread something, it is our exposition failure. "We realize our original text was ambiguous and have revised it as follows..."
- Never dismissive: No bare "we respectfully disagree." Every disagreement must be backed by evidence, data, or a reference.
- Direct answers first: Start each response with what you did ("We have added...", "We agree and now show..."), then explain why.
- Remember the audience: You are writing to the editor, not (only) the referee.
Structure
- Respond to every point: No exceptions, including minor ones.
- Self-contained responses: Quote or paraphrase the revised manuscript text directly in the letter.
- Reference by section name: Not page numbers (which shift between drafts).
- Group related points: When two comments address the same underlying issue, respond jointly.
Substance
- Do what the referee asks, even if you disagree: Run the requested analysis, report results in the letter, then explain why you believe the main text should differ.
- Don't over-revise: Restrict changes to what is requested.
- Address general criticisms globally: If the referee cites two examples, fix the problem paper-wide.
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 · 201 lines · 24 tokens per session scan A 918de47e0bc4
respond-to-referee is a skill published in the GitHub repository Alexander-M-Dickerson/ai-asset-pricing (59 stars, last pushed 4mo ago), licensed MIT. It adds 24 tokens to every session and 1,728 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.
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