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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.
#Recherche#Analyse#Productivité
Note
Davantage d’évaluations nécessaires
Vendus
1
Mode d’utilisation
Exécuter sur Capafy
Aussi sur des applications externes
Fourni par l’éditeur
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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