ingest

This skill should be used when processing raw content (transcripts, documents, notes, current conversation) into structured knowledge nodes for a Context OS. Extracts atomic concepts, creates nodes with complete frontmatter and [[wiki-links]], and routes each node to the correct knowledge_base/ domain. Use when user says "ingest this", "process into knowledge base", "turn this into nodes", or provides raw content to structure. Uses tags consistent with existing graph nodes; new concepts start as status emergent.

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Install skill "ingest" with this command: npx skills add jacob-dietle/skillsmp-jacob-dietle-jacob-dietle-ingest

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Related Skills

Related by shared tags or category signals.

Research

quickstart

This skill should be used when a user wants to build their first Context OS or kick off initial setup of a knowledge graph system. Guides through a 10-minute flow — assess content, create the two-layer directory structure, generate CLAUDE.md, ingest first content, and verify compounding works. Adapts to blank-slate vs existing-content starting points. Use when user says "set up a context OS", "get started with context OS", "build a knowledge graph from scratch", or "quickstart".

Repository SourceNeeds Review

-78jacob-dietle

Automation

coordinated-agent-teams

This skill should be used when decomposing a spec into a multi-agent implementation plan with dependency ordering, parallelism decisions, contract testing, and verification strategy. Applies evidence from 5 verified multi-agent builds (sequential handoff, parallel fanout, mixed waves, corpus-wide single-agent, phased query engine) to prevent the common failure modes — integration surprises, context loss, silent failures, and over-specification overhead. Use when the implementation involves 3+ agents, has parallelization opportunities, or requires handoffs across context windows.

Repository SourceNeeds Review

-78jacob-dietle

Research

outdoor-monitoring-analysis

Detects targets such as people, vehicles, non-motorized vehicles, and pets within target areas; supports batch image analysis, suitable for outdoor surveillance scenarios like courtyards, orchards, and farms. | 户外看护智能监测分析技能，检测目标区域内的人、车、非机动车、宠物等目标，支持批量图片分析，适用于庭院、果园、养殖场等户外区域看护场景

Archived SourceRecently Updated

--18072937735

Research

fall-detection-video-analysis

Detects whether anyone has fallen within a target area. Supports video stream analysis and is suitable for real-time safety monitoring of elderly people living alone. | 跌倒检测视频版技能，检测目标区域内是否有人跌倒，支持视频流检测，适用于独居老人居家安全监测

Archived SourceRecently Updated

--18072937735