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
Recommend AND run open-source AI tools, agents, Claude Code / Codex skills, and MCP servers for any stage of a literature review — searching, reading, extracting, synthesizing, screening, citation-checking, and paper writing. Use when the user asks "what tool should I use to..." OR "install/run/use <tool> to ..." for research/lit-review work: automating a survey or related-work section, PDF→Markdown extraction for LLMs (MinerU/marker/docling), PRISMA / systematic review (ASReview), citation-backed Q&A over PDFs (PaperQA2), wiring papers into Claude/Cursor via MCP (arxiv/paper-search/zotero servers), or chatting with a Zotero library. Ships a launcher (scripts/litrun.py) that installs each tool in an isolated venv and runs it. Curated catalog of 70+ vetted projects. 支持中英文(用于「文献综述工具选型」与「一键安装/运行」)。
development
Route empirical-research requests through the Auto-Empirical Research Skills catalog when this whole repository is installed as one skill in Codex, CodeBuddy, Claude Code, or another IDE. Use to choose and load the right vendored AERS skill for causal inference, econometrics, replication, data acquisition, manuscript writing, peer review and referee responses, citation checking, de-AIGC editing, or full empirical-paper workflows without reading the entire repository at once.
documentation
Use when the project collects primary data or runs a field, lab, or survey experiment, before the intervention begins — write the pre-analysis plan, size the sample from a power calculation, and register with the AEA RCT Registry. Apply after the design is chosen in aer-identification and before any outcome data are seen.
tools
Guide economists to authoritative data sources with explicit, confirmed data specifications before retrieval; interfaces with Playwright MCP to navigate portals and extract real data, not articles about data.