Review Overleaf Agent Skill
This skill should be used when user asks to "fetch overleaf review comments", "address overleaf reviews", "apply overleaf comments", "review my overleaf paper", "sync overleaf feedback to local", "what comments are on my overleaf doc", or wants to act on Overleaf reviewer feedback in a local git-tracked LaTeX repo.
Install
one command, takes just this skill from the repositorynpx skills add https://github.com/fcakyon/claude-codex-settings --skill review-overleafThe instruction itself
9 sections, as written by the authorReview Overleaf
Pull unresolved review threads from an Overleaf project, locate each in the local repo, propose edits the user reviews, and apply them. Does not push back to Overleaf — the web UI is still the place to mark threads resolved after the user verifies the local change.
Step 1: Resolve project ID
Accept any of:
- Raw 24-char hex ID (
^[0-9a-f]{24}$) - Full URL like
https://www.overleaf.com/project/<id>— extract via regex - Project name in quotes — call:
python3 ${CLAUDE_PLUGIN_ROOT}/scripts/overleaf_reviews.py --list-projects
Each line is <24-hex> <accessLevel> <name>. Fuzzy-match the name. If multiple match, AskUserQuestion to disambiguate.
If the user has not given a project ID at all, run --list-projects and show the user the table so they can pick one.
Step 2: Cookie precheck
If ~/.claude/overleaf-skills/cookie does not exist, tell the user to "set up overleaf" (which triggers the setup skill) and stop.
If it exists but auth fails (the next script call returns a refresh hint), point at the same setup skill and stop.
Step 3: Access-level guard
If the project ID came from name resolution, check the matched entry's accessLevel. If readOnly, warn:
> Project is read-only. You can edit local files but cannot sync them back to Overleaf via the web UI; you would need to copy-paste manually. Continue?
For owner, readAndWrite, or review, proceed silently.
Step 4: Fetch comments
python3 ${CLAUDE_PLUGIN_ROOT}/scripts/overleaf_reviews.py --json --repo . < project-id > --unresolved-only
Parses to a JSON array. Each record has: thread_id, doc_id, snippet, offset, resolved, messages (list of {user, ts, content}), file, line. The file and line are null when the snippet did not match any local *.tex.
Step 5: Edit loop
For each record where file is non-null:
Readthe file atline± 5 lines for context.- Summarize the comment thread in one sentence: who said what.
- Propose a concrete edit grounded in the comment text. If the comment is a question (e.g., "did you mean X?"), the edit should answer it in the prose; if it's a correction (e.g., "wrong notation"), the edit should make the correction.
- Apply via
Edit. Do not batch — one comment, one edit, then move on.
Skip records where file is null (snippet did not map). Collect them in an <unmapped> list.
Step 6: Wrap up
After the loop:
- Run
git diffand show the user the full set of changes. - List the
<unmapped>records (if any) withdoc_id+ snippet preview, so the user can hunt them manually. - Suggest a commit message in the style:
address overleaf review: <one-line summary of the changes>. Do NOT auto-commit. The user can run/github-dev:commit-stagedor commit by hand. - Remind the user to mark the addressed threads as resolved in the Overleaf web UI once they verify the local diff.
Non-goals
- No re-upload to Overleaf (no write API used).
- No thread resolution in Overleaf (web UI only).
- No
.bibedits unless a comment specifically targets a citation. - No multi-line snippets that span paragraph breaks — those land in
<unmapped>for v1; the snippet matcher is line-anchored.
Pairs naturally with
github-dev—/github-dev:commit-stagedafter the edit loop,/github-dev:create-prif the project is collaborative.
Other skills for the same job
different authors, same section of the catalogue
Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing network topologies. Applicable to social networks, biological networks, transportation systems, citation networks, and any domain involving pairwise relationships.
Interact with Zotero reference management libraries using the pyzotero Python client. Retrieve, create, update, and delete items, collections, tags, and attachments via the Zotero Web API v3. Use this skill when working with Zotero libraries programmatically, managing bibliographic references, exporting citations, searching library contents, uploading PDF attachments, or building research automation workflows that integrate with Zotero.
Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing network topologies. Applicable to social networks, biological networks, transportation systems, citation networks, and any domain involving pairwise relationships.
Create, analyze, and visualize complex networks and graphs in Python with NetworkX. Use when working with network/graph data structures, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks (random, scale-free, small-world), reading/writing graph file formats, or drawing network topologies. Common applications include social, biological, transportation, and citation networks.
Use NeuroKit2 to build or audit reproducible research workflows for physiological time-series preprocessing, event/interval analysis, multimodal alignment, variability, and complexity. Trigger when code imports neurokit2 or needs its current APIs, schemas, and method-aware validation—not for diagnosis or device validation.
Interact with Zotero reference management libraries using the pyzotero Python client. Retrieve, create, update, and delete items, collections, tags, and attachments via the Zotero Web API v3. Use this skill when working with Zotero libraries programmatically, managing bibliographic references, exporting citations, searching library contents, uploading PDF attachments, or building research automation workflows that integrate with Zotero.
Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing network topologies. Applicable to social networks, biological networks, transportation systems, citation networks, and any domain involving pairwise relationships.
A practical, jargon-free guide to fp-ts functional programming - the 80/20 approach that gets results without the academic overhead. Use when writing TypeScript with fp-ts library.
How to use it
Take fcakyon/review-overleaf from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.