post-manuscript-benchmark-review

name

post-manuscript-benchmark-review

description

Post-draft academic manuscript review against benchmark papers and editorial standards. Use only after an initial full manuscript draft, thesis chapter draft, or journal paper draft exists and the user asks for review, grading, gap analysis, target-paper comparison, SCI/Q1 or Applied Energy-style readiness assessment, desk-reject risk review, page/paragraph/sentence-level audit, benchmark-literature comparison, reviewer-comment response planning, next-version optimization planning, or multi-agent/sub-agent parallel review across scope fit, novelty, scientific logic, evidence support, language audit, citation proximity, figure/format QA, and reviewer-comment action planning. Do not use during outline planning, literature search, figure generation, citation verification, formatting, or de-AI polishing unless a complete draft exists. Chinese triggers: 初版论文后评审, 论文生成后评审, 对标文献差距, SCI一区评审, 论文质量评判, 下一版优化方案, 与对标论文比较, 审稿意见处理, 多agent论文评审, 子agent并行评审, 多智能体稿件审查, 期刊匹配度审查, 创新性审查, 科学逻辑审查.

Post-Manuscript Benchmark Review

Use this skill as a post-draft quality gate. It reviews a complete or substantial academic draft against benchmark papers and produces the next-version revision plan.

Activation Gate

Proceed only when a complete initial manuscript, integrated thesis chapter, or substantial full draft exists.

Do not run this skill for topic selection, outline design, literature discovery before drafting, PDF/DOCX parsing alone, figure/table generation alone, citation verification alone, formatting, or de-AI polishing before a full draft exists. Route those tasks upstream.

Boundaries

Do:

• Judge a full draft against target standards and 3-10 benchmark papers.
• Identify manuscript gaps, claim risks, evidence needs, and next-version P0/P1/P2 actions.
• Analyze reviewer/editor/supervisor comments in the context of a complete draft.
• Produce a ten-dimension 100-point quality review and target-readiness judgment.
• When the user requests an editorial-style SCI/Q1 audit, delegate bounded checks to a standards-review agent for scope fit, novelty, and scientific logic before final judgment.
• Use page, paragraph, and sentence anchors whenever the source format exposes them.

Do not:

• Fabricate benchmark papers, DOI records, journal levels, acceptance probabilities, or benchmark-paper contents.
• Treat abstract-only or metadata-only benchmark information as full-paper evidence.
• Rewrite the manuscript as the primary task; route confirmed revision execution to $revision-control.
• Perform citation identity checks as final authority; route to $academic-research-verification.
• Maintain sentence-level revision state, object libraries, or pass/fail decisions; route to $revision-control.

Intake

Collect draft path/content, target paper type, target journal/school/quality tier, reference list, evidence register, figures/tables, results/data, code or analysis scripts, benchmark papers, reviewer/supervisor comments, and missing-material constraints.

Before reviewing, ask for missing materials that would materially improve review quality:

Required or high-value materials:
Missing materials:
Can proceed without them: yes/no
Fallback if unavailable:

If key inputs are unavailable, produce a provisional review plan and materials request instead of a final readiness judgment.

Workflow

1. Confirm the post-draft gate and review target.
2. Build or validate the 3-10 benchmark set with benchmark-selection-and-extraction.md.
3. Apply the ten-dimension 100-point review, four-criterion diagnostic lens, and claim triage in review-rubric.md.
4. If the user asks for editorial-style SCI/Q1 screening, run standards-review-agent.md and merge its scope-fit, novelty, and scientific-logic findings before the final judgment.
5. Use benchmark-report-schema.md to keep benchmark facts, access limits, manuscript claim records, gap severity, and next-version actions auditable.
6. Use reviewer-comment-response-workflow.md and reviewer-comment-action-plan-gate.md when concrete reviewer, editor, committee, or supervisor comments are provided for a complete draft.
7. Use main-text-and-rebuttal-claim-support-gate.md before approving factual, boundary, subjective, contribution, limitation, or rebuttal judgments.
8. Use cross-disciplinary-language-review-gate.md when formal review output must judge abstract wording, undefined local labels, operation-record prose, sentence purpose, citation proximity, proxy validity, or bilingual claim-strength consistency.
9. Use multi-agent-academic-workflow-gate.md before launching independent review checks for structure logic, evidence support, language gate issues, citation proximity, figure/format QA, reviewer-comment action planning, or editorial-style standards screening.
10. Use review-output-template.md for formal Chinese reports, readiness judgments, benchmark gap tables, standards-audit tables, and next-version plans.
11. Return readiness level, ten-dimension scores, evidence limits, benchmark gaps, standards-audit findings, P0/P1/P2 actions, material requests, rollback risks, and $revision-control handoff packets.

Quality Gate

The review is high quality only if it:

• names exact draft sections, figures, tables, claims, data, code, or evidence-register keys behind each critique;
• separates benchmark facts from inference;
• distinguishes fatal blockers from optional polish;
• gives actions executable in the next manuscript iteration;
• marks missing evidence, benchmark access limits, and material dependencies explicitly.
• turns two or more review comments into a triaged action plan before manuscript rewriting.
• applies the cross-disciplinary language review gate when wording quality, terminology clarity, sentence purpose, or support distance is part of the review.
• plans multi-agent parallel checks by default for substantial benchmark review, language audit, evidence-support review, figure/format QA, or reviewer-comment decomposition, then merges findings before final judgment.
• uses page, paragraph, and sentence anchors whenever the source format exposes them.
• does not directly edit the manuscript; it sends confirmed modification tasks to $revision-control.

Reference

Read benchmark-selection-and-extraction.md when selecting or extracting benchmark papers.

Read review-rubric.md when scoring, gap-analyzing, judging readiness, or triaging claims.

Read benchmark-report-schema.md when producing benchmark material records, manuscript claim records, benchmark gap tables, or next-version action tables.

Read reviewer-comment-response-workflow.md when user-provided review comments must be accepted, partly accepted, rejected with reasons, prioritized, and turned into a next-stage plan.

Read reviewer-comment-action-plan-gate.md when two or more review comments must become concrete modification actions.

Read main-text-and-rebuttal-claim-support-gate.md before treating benchmark, readiness, contribution, limitation, or rebuttal judgments as final prose.

Read cross-disciplinary-language-review-gate.md when reviewing formal body text or rebuttal prose for abstract, mechanical, internally defensive, undefined-term, citation-unclear, proxy-unsupported, or cross-language-inconsistent wording.

Read multi-agent-academic-workflow-gate.md when a complete draft review can be split into parallel checks. Use it for sub-agent scope, output format, confirmation gates, conflict handling, and main-agent merge rules.

Read review-output-template.md when producing a formal report, Chinese evaluation, SCI/Q1 readiness judgment, or benchmark gap table.

Read standards-review-agent.md when the user asks for editorial-style SCI/Q1 screening, desk-reject risk review, Applied Energy-level comparison, or page-by-page, paragraph-by-paragraph, and sentence-by-sentence audit.

Read revision-control-contract.md when turning review findings into a formal revision queue.