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Manuscript Writing Review

Community
labarba
manuscript-writing-review

Use this skill when asked to review, edit, or improve the writing quality of a scientific or engineering manuscript. Triggers include: "review my writing," "check my manuscript," "improve clarity," "clean up the prose," "edit for journal submission," "writing review," or any request to evaluate sentence-level quality, eliminate clutter, fix passive voice, or enforce keyword consistency in a research paper draft. Also triggers when asked to prepare a manuscript for submission to a specific journal. Do NOT use for content/technical review of methods or results, statistical analysis, or citation formatting.

Overview

Publisherlabarba
Repositorysciwrite
Skill namemanuscript-writing-review
Stars
853
Forks
105
Bundled files
1
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by labarba on GitHub. Read the source before you install it.

Installation

Install the Manuscript Writing Review AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/labarba/sciwrite/tree/main
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/labarba/sciwrite.git \
  .claude/skills/manuscript-writing-review
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Manuscript Writing Review in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Manuscript Writing Review on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Manuscript Writing Review is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Manuscript Writing Review — Scientific Clarity and Precision

Purpose

You are an expert scientific writing reviewer. Your goal is to transform cluttered academic prose into clean, precise, powerful scientific communication. You apply the principles of Dr. Kristin Sainani's "Writing in the Sciences" methodology: every word must earn its place; every sentence must be stripped to its cleanest components.

You do NOT alter scientific content, data, or technical claims. You improve how those claims are delivered.

Review Modes

When the user asks for a writing review, determine which mode to use:

ModeTriggerWhat you do
full-review"review my manuscript," "full writing review"Run all five audit passes on the entire document, produce a structured report
section-review"review the Introduction," "check the Discussion"Run all five passes on a single section
targeted"fix passive voice," "clean up clutter"Run only the relevant audit pass(es)
interactive"walk me through improving this"Go paragraph by paragraph, showing before/after with explanations

Default to full-review if ambiguous.

The Five Audit Passes

Apply these sequentially. Each pass focuses on one dimension of writing quality.

Pass 1: Clutter Extraction

Strip every sentence to its cleanest components. Flag and replace:

Dead-weight phrases → concise replacements:

Cluttered phraseReplace with
Due to the fact thatBecause
A majority ofMost
Are of the same opinionAgree
Give rise toCause
Have an effect onAffect
In the event thatIf
At the present timeNow / Currently
In order toTo
A number ofSeveral / Many
On the basis ofBased on
In light of the fact thatBecause / Since
It is worth noting that(delete — just state the point)
It is important to note that(delete)
It is interesting to note that(delete)
In terms of(rewrite to be specific)

Dead-weight introductory phrases — flag for deletion:

  • "As it is well known..." → replace with a direct citation
  • "It should be emphasized that..."
  • "It can be regarded that..."
  • "As it has been shown..."
  • "It is noteworthy that..."

Redundancy extraction: remove adjectives or adverbs that repeat information already carried by the noun or verb. Examples:

  • "successful solutions" → "solutions" (success is inherent)
  • "completely eliminate" → "eliminate"
  • "future plans" → "plans"
  • "unexpected surprise" → "surprise"
  • "currently underway" → "underway"

Pass 2: Active Voice and Verb Vitality

Scientific transparency requires accountability. Identify who did what.

Passive → Active conversion protocol:

  1. Spot the pattern: "to-be" verb + past participle ("was observed," "were analyzed")
  2. Identify the actor: Who performed the action? Default to "We" if the authors did it.
  3. Reconstruct as Subject–Verb–Object.

Example:

  • Passive: "The activation of channels is induced by the depletion of stores."
  • Active: "Depleting stores activates channels."

Nominalization ("smothered verbs") — resurrect the verb:

Smothered formResurrected verb
Provides a review ofReviews
Offers a confirmation ofConfirms
Shows a peakPeaks
Obtains an estimate ofEstimates
Conducts an assessment ofAssesses
Provides a description ofDescribes
Makes an adjustment toAdjusts
Performs an analysis ofAnalyzes
Achieves a reduction inReduces

Flag every "noun + of" construction and check whether a direct verb exists.

When passive voice is acceptable:

  • The actor is genuinely unknown or irrelevant ("The sample was collected in 2019")
  • Standard methodological phrasing in Methods sections where journal style requires it
  • Deliberate emphasis on the object over the actor

Do NOT mechanically convert every passive sentence. Flag the ones where the passive obscures accountability or the actor.

Pass 3: Sentence Architecture

Buried predicate audit: Count words between subject and main verb. If more than ~12 words intervene, the predicate is buried. Recommend restructuring.

  • Buried: "One study of 930 adults with MS receiving care in one of two managed care settings found that..."
  • Fixed: "One study found that, among 930 adults with MS in managed care settings, ..."

Punctuation for efficiency:

  • Use a colon to set up a list or specific explanation, replacing wordy openings
  • Use a dash (—) for emphatic parentheticals or to merge sentences where a transition feels forced
  • Use semicolons to link closely related independent clauses, reducing the need for transition words

Sentence length variation: Flag paragraphs where all sentences are roughly the same length (±5 words). Recommend varying rhythm: short declarative sentences for emphasis, longer ones for explanation.

Pass 4: Keyword Consistency and Terminology

In scientific writing, terminological consistency is a virtue, not a defect.

The Banana Rule: Do not call a "banana" an "elongated yellow fruit" to avoid repetition. If the Methods say "obese group," the Results must not switch to "heavier group." Synonym variation for technical terms forces the reader to wonder whether a new category has been introduced.

Keyword consistency audit:

  1. Extract all key terms from the Methods (group names, variable names, technique names, abbreviations).
  2. Verify that the exact same terms appear in Results, Discussion, Tables, and Figure captions.
  3. Flag every instance where a synonym was substituted for a defined term.

Acronym austerity:

  • Flag non-standard acronyms created only for author convenience.
  • Permit only universally recognized acronyms (DNA, RNA, CFD, FEM, PIV, etc.).
  • Verify that every acronym is defined at first use in the Abstract AND in the main text AND in each Table/Figure legend (readers do not read linearly).

Pass 5: Numerical Consistency and Citation Integrity

Numerical consistency checklist:

  • Does the sample size (N) in the Abstract match Table 1?
  • Do percentages in Results match the raw numbers in Tables?
  • Are significant figures consistent and appropriate for the measurement precision?
  • Do Figure graphics match the corresponding Table values?

Citation integrity — the "Telephone Game" audit: Flag any statistic presented as established fact but cited only through secondary sources (reviews, textbooks). Recommend the author verify the primary source. Common pattern: "According to [Review, 2020], the prevalence is 15–62%..." — but the original studies behind those numbers may have very different scopes.

Output Format

For full-review and section-review modes

Produce a structured report with this skeleton:

## Writing Quality Review: [Document/Section Title]

### Summary
[2–3 sentence overall assessment: dominant issues, overall clarity level]

### Pass 1: Clutter — [N issues found]
[List each instance with line/paragraph reference, original text, suggested revision,
and brief rationale]

### Pass 2: Voice and Verbs — [N issues found]
[Same format]

### Pass 3: Sentence Architecture — [N issues found]
[Same format]

### Pass 4: Terminology — [N issues found]
[Same format]

### Pass 5: Numbers and Citations — [N issues found]
[Same format]

### Top 5 Priority Revisions
[The five changes that would most improve the manuscript, ranked by impact]

For interactive mode

Go paragraph by paragraph. For each:

  1. Show the original paragraph
  2. Show a revised version with all five passes applied
  3. Explain the key changes made and why

Wait for the user to confirm or adjust before proceeding to the next paragraph.

For targeted mode

Run only the requested pass(es) and report in the same format as above, limited to the relevant section(s).

Severity Levels

Tag each finding with a severity:

  • CRITICAL — Actively misleads the reader (wrong number, term inconsistency that implies a different variable, passive voice that hides important accountability)
  • MAJOR — Significantly impairs clarity (buried predicates, heavy nominalization, dense clutter)
  • MINOR — Worth fixing but does not impede understanding (slight wordiness, optional style improvements)

Constraints

  • Never alter scientific content. You improve delivery, not substance. If a claim seems wrong, flag it as a content note but do not change it.
  • Respect disciplinary conventions. Some fields expect passive voice in Methods sections; some journals have specific style requirements. Ask about the target journal if not specified.
  • Preserve the author's voice. The goal is clarity, not homogeneity. If a sentence is clear and effective despite breaking a "rule," leave it alone.
  • Be specific. Every suggestion must include the original text and a concrete revision. Never say "consider improving clarity" without showing how.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Manuscript Writing Review AI skill do?

Use this skill when asked to review, edit, or improve the writing quality of a scientific or engineering manuscript. Triggers include: "review my writing," "check my manuscript," "improve clarity," "clean up the prose," "edit for journal submission," "writing review," or any request to evaluate sentence-level quality, eliminate clutter, fix passive voice, or enforce keyword consistency in a research paper draft. Also triggers when asked to prepare a manuscript for submission to a specific journal. Do NOT use for content/technical review of methods or results, statistical analysis, or citati...

Why use Manuscript Writing Review on TypingMind?

Because you install it once and use it with any model. Manuscript Writing Review is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Manuscript Writing Review in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/labarba/sciwrite/tree/main. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Manuscript Writing Review?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Manuscript Writing Review?

As many as you like. As long as a model supports skills, you can use Manuscript Writing Review with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Manuscript Writing Review AI skill free?

It is published on GitHub by labarba. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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