skills/29-quarcs-lab-project20XXy/dot-claude/skills/referee-response/SKILL.md
Drafts a point-by-point response letter to referee comments with suggested edits. Use after a revise-and-resubmit.
npx skillsauth add brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research referee-responseInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Draft a structured point-by-point response to referee comments.
$ARGUMENTS — path to a file containing referee comments (e.g., notes/referee-report-R1.txt), or the word "paste" to accept inline inputRead the referee comments:
Read index.qmd to understand the current manuscript content, structure, and arguments.
Parse the referee comments into individual points. Each point typically starts with a number, letter, or dash.
For each referee point, draft a structured response:
**Point N:** [Quote or paraphrase the referee's comment]
**Response:** [Address the comment — acknowledge the concern, explain what was done
or why you disagree, provide additional evidence or reasoning]
**Changes made:** [Describe specific edits with section references, e.g.,
"We have added two paragraphs to Section 3 (@sec-data) clarifying the sample selection."]
Use appropriate response conventions:
Organize the response by referee:
# Response to Referee Comments
## Referee 1
[Point-by-point responses]
## Referee 2
[Point-by-point responses]
## Editor
[Point-by-point responses]
Save the response letter to notes/referee-response-R<N>.md where N is the revision round number (check existing files to determine the round).
Generate a separate list of suggested manuscript edits — specific changes to index.qmd or notebooks that address the referee's concerns. Present these to the user but do NOT apply them without explicit approval.
Report the response letter file path and the list of suggested edits.
tools
Autonomous multi-round research review loop using MiniMax API. Use when you want to use MiniMax instead of Codex MCP for external review. Trigger with "auto review loop minimax" or "minimax review".
tools
Autonomous research review loop using any OpenAI-compatible LLM API. Configure via llm-chat MCP server or environment variables. Trigger with "auto review loop llm" or "llm review".
tools
Autonomous multi-round research review loop using MiniMax API. Use when you want to use MiniMax instead of Codex MCP for external review. Trigger with "auto review loop minimax" or "minimax review".
tools
Autonomous research review loop using any OpenAI-compatible LLM API. Configure via llm-chat MCP server or environment variables. Trigger with "auto review loop llm" or "llm review".