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Found 18 Skills
Complete automated literature discovery pipeline: multi-source search → six-dimension scoring → fine reading → formatted delivery → archival. Combines a configurable engine with daily cron-driven application layer. Works with Feishu, Telegram, or any messaging platform.
Standardized Experimental Logging - Accepts raw materials (images/voice/text) and generates standard logs with YAML frontmatter to Obsidian vault. Requires Feishu CLI or manual input for use.
Proposal-first scientific writing pipeline. Three modes (compose/revise/hybrid) with a four-layer QA pipeline. It enforces the principles of evidence-before-prose, argument-before-sections, and contracts-before-paragraphs.
Use when a user needs lawful academic full text, CNKI institutional access, English OA retrieval, publisher API access, institutional browser fallback, or supporting information downloads.
Perform cross-source validation on academic literature entry by entry, compare fields including authors, titles, years, volumes/issue numbers, and page numbers, mark issues such as conflicts between volume year and DOI year, abnormal author order, and page number deviations, and output a structured verification report. It supports batch processing of reference lists in entire papers/proposal reports, single-entry verification, and synchronous correction with Zotero.
Audit, revise, or draft manuscript statistical reporting for Nature / high-impact journal submissions. Use when the user asks to check statistical analysis sections, p values, confidence intervals, sample size, biological versus technical replicates, randomization, blinding, multiple-comparison correction, model assumptions, figure legends, Results statistics wording, reviewer comments about statistics, or Chinese academic drafts needing publication-ready Statistical analysis text. Also trigger on general paper-statistics requests such as 统计审查、统计分析小节、统计方法、p值、样本量、重复数、多重比较、置信区间、效应量、图注统计、审稿人统计意见.