Reviewer comments worked into the article in one run
An article comes back from a journal with reviewer comments. AI makes the edits right in the Word file, replies to the reviewers point by point and checks the result itself, so the editor gets a package ready for submission.
ClientAn agency that prepares journal publications, second project
- Repeat client
- Edits right in Word
- Double-checked result
01Edits right in Word: a new column the reviewer asked for and renumbered citations, in yellow
01Before
A journal returns an article with comments from two or three reviewers. The editor works through every point by hand, edits the text, tables and references, highlights the changes and writes a reply to the reviewers in English, hours per article. One missed point sends it back again, and an ordinary AI chat breaks Word formatting and can invent sources.
02What changed
- Every comment in one run
edits go straight into the .docx: text, tables, references and citation numbering.
- A ready-to-submit package
a clean article, a version with changes highlighted and a point-by-point reply to the reviewers in English.
- Checked by code and by eye
the result is checked against the source and the journal's requirements, and the pages are reviewed the way an editor will see them.
- Nothing is made up
if the author needs to supply data, the article is marked “do not submit yet” and a list of questions comes back.
03How it works
- 01
A team member uploads the article and comments to the chat
- 02
The AI makes the edits right in the Word file
- 03
The system checks the result by code and by eye
- 04
A package ready for submission to the journal
The client is happy: this is already their second project, and the agency says the work helps a lot. A third one is under discussion.
Sample data: a fictional article, authors, journal and comments, processed by the same toolkit the client uses.
The same approach, built for your task
Here it's articles and peer review. Giving AI proper tools and strict checks works for any business buried in complex documents.
- 01Contracts
edits from a lawyer's comments, with highlighted changes and a list of disputed clauses.
- 02Proposals and tender packs
fitting the requirements, recalculating tables, checking before sending.
- 03Reports and policies
updating sections, numbering, checking against the template and your own rules.
- 04No server needed
the tools unpack inside Claude's cloud environment and run on your own subscription.
Show me your most painful document and I'll build the tools for it.
Under the hoodTechnical details for specialists
- The system inside the AI
whatever code can do reliably (file edits, word counts, numbering, checks) is done by code; the model decides what to change and writes the text. That's why the result is repeatable.
- Self-check before each run
the tools pass automated tests before every run, and if anything is off, the work doesn't start.
- Checks by eye
a LibreOffice render step turns every page into an image, so Claude sees the result the way an editor does.
- Readiness gates
until the author supplies what's missing, folders are marked “do not submit yet”: the AI never invents data or sources.
Stack
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