claude

ai-eng-research

Deep research, knowledge capture, and documentation tools

8 on GitHubby v1truv1usv1.14.0MITupdated 2 months agodevelopment
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Plugin ai-eng-research from marketplace ai-eng-system in v1truv1us/ai-eng-system. Commands read from the repo's manifest — 1 month ago.

What it installs

Skills (4)

  • graph-rag

    Relationship-aware retrieval using graph traversal, entity anchors, community expansion, and hybrid vector plus graph search. Use when chunk similarity alone misses paths, entities, or subsystem context.

  • investigation-loop

    Long-running Jira investigation that self-continues past natural stops until a written hypothesis with evidence citations is produced. Pairs with the cooking Stop hook and hard-stops at 10 iterations.

  • knowledge-capture

    Document solved problems with context, examples, and gotchas so learnings compound for the team. Use after completing a workflow worth remembering.

  • multimodal-corpus-ingestion

    Normalize mixed inputs like code, docs, PDFs, screenshots, diagrams, audio, and transcripts into a structured corpus. Use when the task depends on combining multiple artifact types before analysis or retrieval.

Subagents (4)

  • ai-engineer

    Build production-ready LLM applications, advanced RAG systems, and

  • docs-writer

    Write concise documentation pages in required format.

  • documentation-specialist

    Analyze codebases and generate comprehensive technical documentation.

  • ml-engineer

    Build production ML systems with PyTorch 2.x, TensorFlow, and

View source on GitHub

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Core workflow: plan, work, review cycle with research and context engineering

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ai-eng-devops

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ai-eng-plugin-dev

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Meta-tooling for creating plugins, agents, commands, and skills

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ai-eng-learning

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Learning workflows for knowledge mapping, decisions, quality gates, and maintenance reviews

4 skills · 6 commands · 1 agent

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ai-eng-content

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Content optimization, SEO, and communication tools

2 skills · 2 commands · 3 agents

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