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manuscript-optimizer【数据与研究】Use when auditing, restructuring, or revising a research manuscript whose scientific question, claim hierarchy, evidence chain, section logic, figures, terminology, or prose may be unclear or out of sync. Apply before sentence-level polishing, especially for whole drafts, major revisions, resubmissions, overclaiming, experiment-by-experiment Results,…
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Treat scientific writing as reasoning, not decoration. Do not make existing results sound more impressive. Organize the scientific question, evidence, interpretation, and conclusion into a chain that a broad scientific reader can follow and evaluate.
Use this priority order without exception:
scientific correctness > logic > information structure > clarity > concision > style
Prefer the simplest sentence that preserves the full scientific meaning. Never polish prose built on an unstable claim, a missing evidence link, or a false scientific premise.
Use this skill above the sentence level. Own the paper's scientific direction, claim architecture, evidence boundaries, section and paragraph functions, figure-text logic, and terminology.
scientific-writing after the architecture is stable to draft or rewrite full prose.write-scientific-manuscript to repair paragraph-level clarity and local reasoning.anti-defensive-writing once the claims are stable, to remove audit, defensive and
self-critical writing from the main text and SI.scientific-prose-style last for punctuation and rhythm.results-section-revision only when the claims are stable and Results needs local flow repair.review-article-architecture instead for a Review, survey, or Perspective.For review-only requests, diagnose and stop. For revision requests, diagnose first and then edit in the macro-to-micro order below.
Preserve the scientific record. Never:
When the evidence is missing, state the gap. Do not fill it with language. If a design or implementation flaw invalidates a result, stop interpreting that result and report the flaw.
Three readers decide what a paper must say: the editor who decides whether it goes to review, the
reviewer who checks the evidence, and the broad peer who reads it after publication. The target
venue decides who they are and what they check. Frame the front matter for the editor and the
broad peer (大同行), a scientist outside the subfield who did not build this kind of method, and
keep every claim in it checkable by the reviewer. For a computational-biology paper in a journal,
the broad peer is a biologist who would use the method but does not know its benchmarks, metrics
or model families. A reader who knows "the broad AI domain" is an adjacent specialist. Writing for
that reader is the usual reason a manuscript reads as too technical. The Readers section of
paper-workflow's references/section-contracts.md says which positions carry this register and
how to test them.
At this layer, check framing before wording: whether the reader meets a problem they recognise as theirs by the second sentence, whether success is measured against what the reader relies on (experiment, expert annotation, known biology) where the data allow it, and whether findings are stated as what was predicted or recovered rather than as metric gains. Framing a finding this way keeps its numbers: the scale of the evidence and the size of the gain stay, with what they measure.
Do not assume that the reader knows:
Supply only the information required to understand the next logical step. Minimize reader inference without turning the manuscript into an experimental log or a tutorial.
Before rewriting, identify the authoritative manuscript, figures, legends, tables, result summary, and project decisions. Preserve citations, figure references, numbers, symbols, and formatting.
Separate the input into three classes:
Do not present an assumption as a confirmed fact. Ask for missing information only when it would materially change the scientific conclusion or revision direction; otherwise flag it and continue.
Write one sentence for each item:
Look beneath model comparison when appropriate. Ask whether measurement, identifiability, data resolution, task formulation, or evaluation design is the actual limiting issue.
If the main claim cannot be stated accurately in one sentence, do not begin prose revision.
Create this artifact before restructuring a whole manuscript:
North Star
└── Central scientific question
└── Main claim
├── Claim 1
│ └── Evidence: result / figure / table / analysis
├── Claim 2
│ └── Evidence: result / figure / table / analysis
├── Claim 3
│ └── Evidence: result / figure / table / analysis
└── Boundary conditions and unresolved points
Use the architecture across the paper:
Do not force three claims when the paper supports two, and do not present several contributions as equally central unless the evidence and design require that structure.
Extract substantive claims from the title, abstract, introduction, Results headings, figure legends, and discussion. For each claim, record its exact support and mark it:
Use the claim ladder:
observation → empirical pattern → interpretation → mechanism → general principle
Write only at the highest level directly licensed by the evidence. Distinguish, for example,
performed best under the evaluated settings from is the best representation.
For a claim that exceeds its evidence, take one of three actions:
Calibrate the claim itself instead of making an inflated statement and retracting it through a
defensive caveat. Use This pattern is consistent with... or One possible explanation is...
when a mechanistic interpretation lacks a direct mechanism experiment.
For each section, state its one-sentence function. For each paragraph, record:
Move, merge, split, or remove material that cannot be mapped cleanly. Organize Results by questions and answers, not by the chronological order of experiments or panels.
Choose the edit depth only after this audit:
Do not default to preserving the original sentence or paragraph structure.
Assign every figure and panel one primary role: claim-supporting evidence, definition or methodological bridge, validation in a new setting, practical consequence, or case illustration. A panel that documents an interface, compatibility or eligibility check (which methods accept which inputs) has none of these roles; it belongs in an SI table or one Methods sentence.
Check that:
Create a canonical term list for core concepts, tasks, settings, datasets, models, baselines, and abbreviations. Use one primary term per concept. Change terms only when the scientific level truly changes; do not rotate synonyms merely to avoid repetition.
After the architecture is stable, revise in this order:
Run a final skeptical review across contribution sufficiency, scientific clarity, empirical strength, evaluation completeness, and method or framework soundness. Point to evidence rather than answering from intuition.
Each position (Title, Abstract, Introduction, Results, Discussion, Methods, legends and SI) is held
to its contract in paper-workflow's references/section-contracts.md, which also gives the order
in which positions depend on one another. Read the entries for the sections under revision; this
skill does not restate them.
At this layer, check three things for each section: whether it does its contract's job, whether it restates a claim that has since moved upstream, and whether it claims more than the evidence it depends on. Revise the positions that compress the argument (Abstract, Title and the final Introduction paragraph) only after the claims they compress are settled.
Use the paragraph as the basic logical unit. Give it one main job and, when appropriate, this form:
topic sentence → evidence → interpretation → transition or implication
Make the first sentence explain why the paragraph exists. Prefer the scientific message to the experimental action. Do not force every paragraph into the template when another order is clearer.
State important inference explicitly. If observations A, B, and C support a modality-dependent effect, write that conclusion instead of asking the reader to assemble it.
Use common, precise words and concrete scientific nouns. Prefer verbs to nominalizations. Avoid
noun stacks such as representation architecture robustness evaluation analysis. Keep one main
logical relationship per sentence. Split a sentence that simultaneously introduces background,
describes a method, reports numbers, interprets the result, and qualifies the claim.
Do not replace readable prose with a sequence of fragments. Align syntactic units with logical units, and retain technical distinctions that change the scientific meaning.
Reject or rewrite these patterns unless the evidence and context specifically justify them:
We evaluated... We found... We also found... In addition...;We did A and B. We observed C and D. Therefore, X without the missing link;To further investigate...;stable performance regimes, intrinsic quality, or
comprehensive superiority when ordinary words are more exact;remarkably, notably, encouragingly, and promisingly;optimal, general, robust, fundamental, transparent, or
state-of-the-art without evidence covering that scope;Do not ban a word mechanically. Reject it when it obscures meaning, inflates the claim, or adds no scientific information.
Before accepting any revised paragraph, answer:
If question 1, 2, or 3 has no clear answer, restructure the paragraph. If question 4 is yes, narrow the claim or obtain evidence. If question 5 is no, add the missing bridge. If question 6 is yes, delete the excess: repetition, reassurance and process narration go; numbers, n, controls and null results are never "excess".
For a manuscript audit, report in this order:
For an authorized revision, add:
Do not claim that a manuscript or section is improved merely because the prose is smoother. Claim completion only after the evidence chain, information structure, terminology, and revised text have been checked together.