verify-translation
Capture all manual pages and verify translations match page images using AI-powered checking. Identifies extraction failures and can regenerate extracted text from images.
Capture all manual pages and verify translations match page images using AI-powered checking. Identifies extraction failures and can regenerate extracted text from images.
Expert technical document reviewer. PROACTIVELY review ADRs, Design Docs, and RFCs for quality, completeness, and principle alignment after creating or updating technical documents.
Paper reading and analysis framework using Moonshot AI (Kimi). Actions: download, analyze, read, summarize, implement papers from arXiv, SIGGRAPH, etc. Features: intelligent paper fetching, AI deep analysis, personalized reading guidance, knowledge internalization, code generation. Supports: PDF parsing, multi-dimensional analysis (summary, innovation, methodology, implementation), structured notes, knowledge graphs, code framework generation.
Validates that book chapters align with the core theme. Use when user says 'check theme alignment', 'does this fit the theme', 'verify alignment', or automatically after every 2 chapters are drafted.
Extract structured knowledge from neurosurgical and spine surgery textbooks. Identifies anatomical structures, surgical procedures, complications, and clinical relationships. Use when processing medical PDFs, building surgical knowledge graphs, or creating clinical decision support content. Applies kaizen continuous improvement from prior extractions.
This skill provides specialized tools for searching and retrieving Islamic classical texts from the Turath.io API and local metadata database. Use this skill when researching Islamic literature, finding book references, extracting page content, or creating content based on classical Islamic texts.
Search code and documentation using full-text and semantic search. Accepts a query string and returns matching files with relevance scores.
Detect clinical note sections (HPI, ROS, Assessment, Plan) using regex patterns and LLM topic segmentation. Generates ToC with accurate byte offsets.
Three-pass critical reading framework for systematic document analysis. Supports tech blogs, retrospectives, technical documentation, personal writing, and academic papers. Primary focus on Third Pass critical analysis, context validation, and actionable reconstruction. Use when analyzing complex documents, performing critical reading, extracting actionable insights, or conducting deep analysis. Triggers include Third Pass, 비판적 분석, critique, 깊이 읽기, 심층 분석.
Read and extract content from PDF files using multiple methods. LOAD THIS SKILL WHEN: User says "讀取 PDF", "read PDF", "打開論文", "看這篇" | has PDF file path | needs to extract text from PDF. CAPABILITIES: PDF to markdown conversion, text extraction, figure detection, citation extraction.
Apply RLM (Recursive Language Model) reasoning pattern for large context processing. Use when analyzing large files, codebases, or documents. Triggers on "RLM pattern", "large file analysis", "selective reading", "PROBE EXTRACT CONFIRM", or when dealing with files over 1000 lines.
Analyzes all documents in a folder and creates a comprehensive summary. Use when asked to summarize documents, understand a collection of files, get an overview of materials, or analyze what's in a folder.
Creates text-based visualizations and reports showing the relationship between spelling errors and semantic distance. Use when you need to visualize experimental results.
Proteomics analysis toolkit for label-free quantitative proteomics. Invokes R scripts for normalization, visualization (volcano, heatmap, PCA, LOPIT), pathway analysis (KEGG, ConsensusPathDB), and protein list cross-referencing (MISEV2018, SASP, Matrisome). USE WHEN user says 'analyze proteomics', 'volcano plot', 'normalize protein data', 'pathway enrichment', 'check EV markers', 'SASP analysis', 'matrisome', OR mentions q-value, fold-change, or protein quantification.
A high-performance skill for processing genomic data (VCF, FASTA, BED) using polars-bio. Features streaming VCF processing, interval joins, FASTA analysis, and variant annotation.
Apply the GRADE framework to assess certainty of evidence in systematic reviews. Use when users need to rate evidence quality, create Summary of Findings tables, or understand the factors that affect confidence in effect estimates.
Patterns for analyzing, improving, and documenting Jupyter notebooks for scientific data analysis. Includes data filtering, visualization optimization, and resource analysis techniques.
Single-cell analysis patterns with AnnData and Scanpy. Use when working with single-cell RNA-seq data, creating or manipulating AnnData objects, performing quality control, normalization, dimensionality reduction, clustering, or visualization of single-cell datasets.
Use when performing meta-analysis, pooling study data, generating forest plots, funnel plots, assessing heterogeneity, or conducting subgroup and sensitivity analyses. Invoke for any statistical synthesis of multiple studies.
Explore Hive tables and datasets in the Wellcome Collection data warehouse. Use this skill to query tables, understand schemas, or analyze data distributions. Invoke with /data-explore.