Context Fidelity
Version: 1.0.0
Last updated: 2026-07-16
Purpose
Deliver the minimum authorized evidence needed for the current task while preserving provenance and freshness.
Why
“Signal-to-noise” is a useful metaphor, not a universal formula. Relevance, completeness, authority, freshness, and conflict handling must be evaluated separately; shorter context can still omit decisive evidence.
How
- Derive required evidence from task acceptance criteria.
- Filter by tenant and user authorization before ranking.
- Rank by task relevance and source authority.
- Preserve source ID, timestamp, version, and trust class.
- Detect conflicts and force abstention or review.
- Measure answer correctness, citation support, retrieval recall, latency, and cost.
{"source_id":"policy-17","version":"4.2","effective_at":"2026-06-01","trust":"authoritative","content":"..."}
When
Use for retrieval, code assistants, multi-turn systems, and any task assembled from multiple sources.
Tradeoffs
| Choice | Benefit | Cost |
|---|---|---|
| Aggressive filtering | Lower cost and distraction | Recall risk |
| Rich provenance | Better attribution | More tokens |
| Freshness checks | Current answers | Source latency |
Anti-Patterns
- Optimizing token count without measuring evidence recall.
- Ranking before access control.
- Mixing policy, user claims, and web text without trust labels.
- Treating a single scalar “fidelity” score as sufficient.
Enterprise Considerations
Enforce row-level tenant controls, source retention policy, legal holds, geographic restrictions, and auditable lineage from output claim to source version.
Checklist
- Required evidence is defined
- Authorization precedes ranking
- Provenance and freshness are preserved
- Conflicts trigger deterministic handling
- Recall and grounded correctness are evaluated
Changelog
- 1.0.0 (2026-07-16): Defined multidimensional context fidelity.
Version: AIES v1.0.0✏️ Edit this page on GitHub