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research-engine

Autonomous research pipeline — topic to structured documents with HTML/PDF output. Proven at HEL (28 docs, 91K words) and OOPS (9 docs, 20K words) scale.

65estrelas
Atualizado há 4 meses

Ver no GitHub ↗ Licença: NOASSERTION

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Research Engine

Activates when user requests deep research, investigation, or analysis of a topic that will produce multiple structured documents.

Pipeline

TOPIC → DECOMPOSE → PARALLEL RESEARCH → AGGREGATE → STRUCTURE → BUILD → PUBLISH

Stage 1: Decompose

Break the research topic into 4-12 investigation tracks. Each track becomes one document.

Stage 2: Parallel Research

Launch research agents (2-6 in parallel) with specific investigation briefs. Use run_in_background: true for independence.

Stage 3: Aggregate

Collect findings. Check for contradictions. Identify cross-references.

Stage 4: Structure

Organize into a numbered document series with:

  • Index page (index.html)
  • Individual research documents (research/NN-slug.md)
  • Knowledge graph (knowledge-nodes.json)
  • Retrospective (retrospective.md)

Stage 5: Build

Convert markdown to HTML and PDF using pandoc + xelatex:

bash build.sh  # Uses template.tex and html-template.html

Stage 6: Publish

Commit, tag, merge to main, push, create GitHub release, FTP sync to configured remote host.

Quality Standards

  • Minimum 1,500 words per document
  • Every claim needs evidence or explicit reasoning
  • Cross-references between documents
  • Fact-check pass before final publish
  • Three output formats: markdown (source), HTML (reading), PDF (sharing)

Project Codes

Each research project gets a 3-4 letter code added to series.js:

  • HEL (Helium Supply Chain)
  • OOPS (Ecosystem Alignment)
  • OPEN (Unsolved Problems)

Build Infrastructure

Templates at the project level:

  • template.tex — LaTeX template for branded PDFs
  • html-template.html — Standalone HTML template
  • build.sh — Automated pandoc build script
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