Data Fidelity

Activates when research documents need verification, fact-checking, or data updates.

When to Use

• After initial research documents are written (quality gate before publish)
• When refreshing documents with current data (market prices, company stats)
• When a user says "check for errors", "verify claims", "fact check", "add fidelity"

Workflow

Phase 1: Fact-Check Fleet

Launch 2-3 parallel fact-checker agents, each covering a different document range:

• Agent A: docs 01-12
• Agent B: docs 13-24
• Agent C: forward-looking/speculative docs (if any)

Phase 2: Aggregate Findings

Collect reports. Categorize by severity:

• ERROR — factually wrong, must fix
• QUESTIONABLE — might be wrong, needs verification
• INCONSISTENCY — contradicts another document

Phase 3: Data Refresh

Launch market-researcher agents for current pricing, company data, and industry stats.

Phase 4: Apply Corrections

Systematic edit pass:

1. Fix all ERRORs first
2. Resolve INCONSISTENCYs (pick the correct value, update all occurrences)
3. Update data with fresh market research
4. Flag QUESTIONABLE items that couldn't be resolved

Phase 5: Rebuild

If documents have HTML/PDF output, rebuild after corrections:

bash build.sh

Quality Standards

• Every numerical claim should have a source or explicit reasoning
• Cross-document consistency: same number must be the same everywhere
• Dates should be specific (not "recently" — say "March 2026")
• Company names should be current (post-merger names, current HQ)
• Legal citations should include statute number (USC, CFR, RCW)