Analyze eval results, diagnose low-scoring criteria, fix tile content, and re-run evals — the full improvement loop automated
94
90%
Does it follow best practices?
Impact
100%
1.02xAverage score across 5 eval scenarios
Passed
No known issues
Eval Bucket Classification
Bucket A: idempotency key
100%
100%
Bucket B: webhook signature
100%
100%
Bucket C: HTTP status codes
100%
100%
Bucket B: currency precision
100%
100%
Bucket D: API version pinning
100%
100%
Bucket D highest priority
100%
100%
Bucket B diagnosis present
100%
100%
Bucket C action suggested
50%
100%
Bucket A no-action
87%
100%
80% threshold applied
80%
100%
Targeted Tile Editing
Explicit retry intervals
100%
100%
Rubric language used
100%
100%
HMAC section unchanged
100%
100%
TLS section unchanged
100%
100%
Observability section unchanged
100%
100%
Processing section unchanged
100%
100%
Retry section only changed
100%
100%
Concise addition
100%
100%
Max retry count preserved
100%
100%
Fast acknowledgement preserved
100%
100%
Cross-file Contradiction Detection
Retry count contradiction found
100%
100%
Auth failure contradiction found
100%
100%
All three files referenced
100%
100%
File attribution per contradiction
100%
100%
Auth contradiction despite scope
100%
100%
Verbatim quotes included
100%
100%
Regression Root Cause Analysis
Contradicting clause identified
100%
100%
Contradiction mechanism explained
100%
100%
Remove/clarify approach taken
100%
100%
Specific text targeted
100%
100%
No compensating additions
100%
100%
Other sections preserved
100%
100%
Pre-review list intact
100%
100%
Redundant Criteria Management
All redundant criteria identified
100%
100%
Options presented per criterion
100%
100%
Useful criteria preserved
100%
100%
Weight redistribution correct
100%
100%
80% threshold applied
100%
100%
Non-redundant scores unchanged
100%
100%
Below-threshold excluded
100%
100%
Removal option named explicitly
100%
100%