E06 · Quality evidence first
Synthetic practice, not company performance.
One decision
Can reviewed acceptance justify expansion?
Run the exact query
WITH b AS (SELECT * FROM v_task WHERE ('all'='all' OR persona='all') AND ('all'='all' OR workflow='all') AND ('all'='all' OR substr(signup_at,1,7)='all') AND date(created_at)>='2026-05-01' AND date(created_at)<'2026-10-01') SELECT workflow,COUNT(*) tasks,SUM(preview_at IS NOT NULL) previews,COUNT(reviewed_at) reviewed,100.0*COUNT(reviewed_at)/NULLIF(SUM(preview_at IS NOT NULL),0) coverage_pct,100.0*SUM(accepted=1)/NULLIF(COUNT(reviewed_at),0) acceptance_pct,SUM(critical_error) critical_errors FROM b GROUP BY workflow;
Download SQL · Result CSV · Metabase saved question
Chart and reading
Read review coverage, acceptance and critical-error counts together.
Challenge your recommendation
Who did not review, and why?
Guardrails: Reviewed acceptance is selected; missing review remains unknown.
Next evidence: Representative bilingual labels, sampling mechanism and hard-case evidence.
PRD sections: 12, 13, 14. Open proposed PRD
Your spoken decision
State one takeaway, one caveat and one action in 30 seconds. Then stop.
Connect this finding
What this chart helps decide · Follow the connected decision · Canonical metric definitions
Optional model answer — try your own first
E06 · Quality evidence first
Decision: Can reviewed acceptance justify expansion?
Readout: Read review coverage, acceptance and critical-error counts together.
Actual query output (synthetic), first rows:
| workflow | tasks | previews | reviewed | coverage_pct | acceptance_pct | critical_errors |
|---|---|---|---|---|---|---|
| api_template | 390 | 289 | 187 | 64.70588235294117 | 79.67914438502673 | 9 |
| document_avatar | 373 | 257 | 172 | 66.92607003891051 | 76.74418604651163 | 11 |
| dubbing | 318 | 216 | 158 | 73.14814814814815 | 70.25316455696202 | 11 |
Model spoken answer: I would not extrapolate reviewed acceptance until I understand missing reviews and critical failure slices.
Caveat/counterargument: Who did not review, and why? Reviewed acceptance is selected; missing review remains unknown.
Next evidence: Representative bilingual labels, sampling mechanism and hard-case evidence.
Deliberately left out: A platform-wide accuracy claim from selected reviews.