knowledge-mining

name	knowledge-mining
description	Use when turning a corpus into reusable, monetizable, verifiable knowledge assets: entity-event-issue extraction, claim libraries, evidence maps, reusable briefs, ontology seeds, dossiers, and refresh cadences.
metadata	{"portable":true,"compatible_with":["claude-code","codex"]}

Knowledge Mining

Use When

• Use when the goal is deep reusable knowledge, not just one report.
• Use after source verification and before knowledge productization.
• Use when building claim libraries, evidence maps, dossiers, reusable briefs, or refreshable intelligence assets.

Do Not Use When

• The project is a one-off deliverable with no reuse path.
• The corpus has not yet passed verification.

Knowledge Mining Required Context

• Verified sources, claim graph, audience needs, target products, and reuse constraints.
• Sensitivity, confidentiality, and commercial boundaries.

Knowledge Mining Core Method Notes

1. Ingest the corpus by source, entity, event, issue, geography, and time.
2. Extract reusable claims and link them to evidence.
3. Build entity-event-issue maps.
4. Identify reusable frameworks, templates, visuals, and briefs.
5. Mark sensitivity and reuse limits.
6. Define refresh cadence and change triggers.
7. Hand the asset portfolio to productization.

Quality Standards

• Every reusable asset keeps provenance.
• Reuse boundaries are explicit.
• Knowledge assets have buyers, users, or decisions attached.
• Refresh logic is defined for time-sensitive claims.