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Research Context Management

Research Context Management

by: Spann
Research Context Management helps agents run long, evidence-heavy research without losing sources, claims, contradictions, or next steps. It builds a durable workspace with a source ledger, batch notes, claim matrix, contradiction register, working brief, and handoff checkpoint, so deep research, audits, market scans, and reports can be reviewed, resumed, and turned into reliable outputs with clearer evidence trails.
#研究#分析#生產力
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使用方式
在 Capafy 上執行
也可用於外部應用程式
由創作者提供
GPT-5.5

Research Context Management

Research Context Management helps agents run long, evidence-heavy research without losing sources, claims, contradictions, or next steps in chat history.

It creates a durable research workspace with:

  • source_ledger.jsonl for source tracking
  • batch_notes.md for detailed source notes
  • claim_matrix.md for mapping claims to evidence
  • contradiction_register.md for conflicts and uncertainty
  • working_brief.md for the current synthesis
  • handoff_checkpoint.md for clean continuation across sessions

Best For

  • Deep research projects
  • Source-grounded reports
  • Conflicting evidence reviews
  • Long-running investigations
  • Research that needs handoff between agents, models, or sessions

Example Output

Source Ledger Entry

{
  "title": "Platform Documentation",
  "url": "https://example.com/docs",
  "publisher": "Example Platform",
  "access_date": "2026-05-28",
  "source_tier": "official",
  "key_claims": [
    "Defines the current API behavior",
    "Lists supported status values"
  ],
  "why_it_matters": "Primary source for platform behavior."
}

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