global-reviewer

Solid

Global consistency review for survey drafts: terminology, cross-section coherence, and scope/citation hygiene. **Trigger**: global review, consistency check, coherence audit, 术语一致性, 全局回看, 章节呼应, 拷打 writer. **Use when**: Draft exists and you want a final evidence-first coherence pass before LaTeX/PDF.

Code & Development 506 stars 39 forks Updated today

Install

View on GitHub

Quality Score: 81/100

Stars 20%
90
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
0
Description 5%
100

Skill Content

# Global Reviewer (survey draft) Purpose: make the draft read like a coherent paper (not stitched subsections) and make problems **auditable**. ## Role cards (use explicitly) ### Consistency Reviewer (auditor) Mission: find cross-section issues a real reviewer would flag, and route them to the right upstream fix. Do: - Check scope/taxonomy consistency and terminology drift across chapters. - Flag underspecified claims (numbers without task/metric/constraint). - Treat missing evidence as a failure signal; route upstream. Avoid: - Writing around gaps by adding new claims or citations. ### Coherence Editor (bridge finder) Mission: spot stitched-island structure and front-matter weaknesses that cause it. Do: - Identify where transitions/leads are doing planner talk instead of argument bridges. - Flag repeated evidence-policy disclaimers and point to front matter as the single home. Avoid: - Style-only nitpicks that do not change readability or verifiability. ## Role prompt: Consistency Reviewer (AI paper reviewer mindset) ```text You are a meticulous reviewer for a survey manuscript. Your job is to surface cross-section problems that would matter to a real reader/reviewer: - missing or underspecified evidence for claims - scope drift and taxonomy inconsistency - weak front matter (boundary/methodology not stated, so H3s carry repeated disclaimers) - stitched-island structure (no argument chain across sections) Constraints: - do not invent facts or citations - do ...

Details

Author
WILLOSCAR
Repository
WILLOSCAR/research-units-pipeline-skills
Created
8 months ago
Last Updated
today
Language
Python
License
None

Similar Skills

Semantically similar based on skill content — not just same category

Data & Documents Solid

draft-polisher

Audit-style editing pass for `output/DRAFT.md`: remove template boilerplate, improve coherence, and enforce citation anchoring. **Trigger**: polish draft, de-template, coherence pass, remove boilerplate, 润色, 去套话, 去重复, 统一术语. **Use when**: a first-pass draft exists but reads like scaffolding (repetition/ellipsis/template phrases) or needs a coherence pass before global review/LaTeX.

506 Updated today
WILLOSCAR
AI & Automation Listed

reviewer

Use ONLY when the user explicitly invokes /reviewer (literal slash command). Performs a native, findings-first review with a deterministic coverage audit run by the reviewer before emission (`scripts/fact_pack.py` + `scripts/audit.py`). Three evidence lanes (defect-hunter, test-auditor, verifier) run delegated or in-context depending on host capability; scout is discretionary. During validation this skill must NOT match generic "code review" requests.

5 Updated today
paulocorcino
AI & Automation Listed

rigorous-paper-reviewer

Review a LaTeX research paper for mathematical rigor, notation consistency, proof obligations, numerical-analysis discipline, complexity claims, convergence/error bounds, figure quality, reader-state flow, cross-references, and global coherence. Use when the user wants a deep technical review or verification pass on a paper, supplement, or LaTeX project; also trigger when the user asks whether text sounds wasteful, machine-generated, clear, simple, readable, well-flowing, compressed, rhythmic, or wants to zoom in/out paragraph by paragraph. Do not use for initial drafting unless the user explicitly asks for review-first feedback.

1 Updated 6 days ago
shubham0704