文档分析器
Deep document structure analysis and intelligent content extraction for knowledge bases.
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158 skills found
Deep document structure analysis and intelligent content extraction for knowledge bases.
Generates llms.txt and llms-full.txt files to provide LLM-friendly documentation and project context.
Comprehensive AI-generated text detection framework. Features multi-layer analysis of vocabulary, structural patterns, model-specific fingerprints, and technical metadata artifacts to identify AI authorship.
Normalizes testing defect logs by correcting typos, abbreviations, and ambiguous descriptions based on product-specific codebooks and station validation.
Fetch and parse transcripts from YouTube and Bilibili videos for summarization, QA, and content extraction using yt-dlp.
Analyze AppWorld task failures to extract specific API patterns and generate actionable playbook bullets with concrete code examples.
Unified content extraction and action planning engine. Automatically processes URLs (YouTube, articles, PDFs) into actionable plans.
Upstash Vector DB setup, semantic search, namespaces, and embedding models. Ideal for building high-performance vector search features in Next.js 16/Vercel projects.
Guidelines for curating high-quality datasets for LLM post-training (SFT/DPO/RLHF), covering data formats, quality filtering, and collection strategies.
Read and navigate external documentation efficiently using llms.txt, MCP search, and smart parsing strategies.
Aggressively prune grammatical scaffolding and filler text from inputs to optimize LLM token usage while retaining core semantic content.
Manage automatic model routing for Higress AI Gateway via CLI. Configure triggers for intelligent model selection based on request content.