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SkillsMP는 joshua-zyy/academic-paper-writer에서 8개의 skill을 수집했습니다. skill을 열어 소스와 세부 정보를 확인하세요.
수집된 skill 8개 중 8개를 표시합니다.
Search, verify, and map citations for CS/AI/ML papers. Produces VERIFIED/UNVERIFIED reference lists with Citation-to-Claim maps and Exemplar Sets. Use when: finding references for a paper section, verifying citation accuracy, building exemplar sets for…
원문 언어: 영어
Use when writing or revising CS/AI/ML papers from research notes, code repositories, local literature libraries, target venue requirements, or section-level drafting requests. Triggers include 写论文, 初稿, paper draft, write introduction, write method, full paper…
원문 언어: 영어
Polish academic prose, de-AI-ify text, control claim strength, or rewrite method sections for CS/AI/ML papers. Executes Prose Quality Gate, Claim Strength Audit, and de-AI pass. Use when: removing AI writing patterns from paper text, adjusting claim strength…
원문 언어: 영어
Self-review, audit, or verify CS/AI/ML paper drafts as a critical peer reviewer. Three-round review (evidence→argument→style) with Verification Status and debt tracking. Use when: reviewing a paper draft before submission, checking evidence compliance of…
원문 언어: 영어
Research target venue requirements and writing style for CS/AI/ML papers. Produces venue-brief.md with submission requirements and detailed writing style analysis. Use when: researching target journal/conference requirements, analyzing writing style of target…
원문 언어: 영어
Use when working on academic paper LaTeX layout, figure/table float placement, draft-to-template LaTeX generation, existing .tex project layout repair, figures piling up, figures far from text, large blank areas, two-column figure/table placement, page-limit…
원문 언어: 영어
Create, revise, or audit academic data/result figures for CS/AI/ML papers. Data/result plots default to Python-generated editable SVG with CS/AI/ML-specific design rules for benchmarks, ablations, training dynamics, robustness, diagnostics, distributions,…
원문 언어: 다국어 혼합
Audit, run, or verify experimental evidence for CS/AI/ML papers. Produces Evidence Inventory with evidence_type annotations (newly_run/preexisting_artifact/user_claim) and Protocol Risk assessments. Use when: checking if experiment results are reproducible,…
원문 언어: 영어