| name | nuggetizer-verify |
| description | Use when validating nuggetizer batch outputs — checks JSONL integrity, duplicate qids, missing nugget fields, assignment label validity, and metrics consistency. Wraps `nuggetizer validate` plus custom assertions. Use after running create, assign, or metrics to verify output correctness. |
Nuggetizer Verify
Validates nuggetizer batch outputs for correctness, completeness, and consistency.
When to Use
- After
nuggetizer create — verify nugget output integrity
- After
nuggetizer assign — verify assignment labels and nugget coverage
- After
nuggetizer metrics — verify metric ranges and qid completeness
- Before submitting results for evaluation or comparison
What It Checks
JSONL Integrity
- Every line is valid JSON
- No trailing commas, no truncated records
- Consistent field presence across records
Create Output
- Every record has
qid, query, and nuggets array
- Every nugget has
text (non-empty string) and importance (vital or okay)
- No duplicate
qid values
- No empty
nuggets arrays
Assign Output
- Every record has
qid, query, and nuggets array with assignment field
- Assignment labels are valid:
support, partial_support, not_support (3-grade) or support, not_support (2-grade)
- No mixed assignment modes within a single file
- Every nugget retains
text and importance from creation
Metrics Output
- Every record has
qid and all four score fields
- Scores are in [0.0, 1.0] range
strict_* scores ≤ corresponding non-strict scores
vital_score computed only over vital nuggets (not all)
Usage
Run the verification script:
bash .claude/skills/nuggetizer-verify/scripts/verify.sh <artifact-path> [artifact-type]
Or use the built-in validator first:
nuggetizer validate create --input-file nuggets.jsonl
nuggetizer validate assign --contexts answers.jsonl --nuggets nuggets.jsonl --input-kind answers
Then run custom assertions via the verify script.
Verification Script
See scripts/verify.sh for the runnable verification wrapper.
Gotchas
nuggetizer validate checks input contracts (before running). The verify script checks output artifacts (after running).
- A record with
importance: "failed" on a nugget indicates a scoring failure — the nugget was created but not successfully scored.
--resume can produce files with records from different model versions if the model flag changed between runs. Check trace.model consistency if --include-trace was used.
- Metrics require assign output as input. Running metrics on create output will fail silently or produce meaningless results.