{ "metrics": [ { "id": "DB01", "name": "Weekly quality-value accounts", "meaning": "Fund repeatable customer value", "business_decision": "Fund repeatable customer value", "formula": "COUNT(DISTINCT account_id)", "unit": "accounts", "grain": "account-week", "numerator": "Accounts with accepted, no-critical-error output and confirmed use", "denominator": "None; count", "eligible_cohort_window": "UTC Monday\u2013Sunday of confirmed_use_at; only complete weeks", "exclusions": "Internal/test/bot accounts in production; absent in fiction", "data_event_source": "v_task; review + use events", "owner": "Product", "leading_lagging": "lagging value", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Do not interpret a selected cohort as population prevalence.", "known_bias": "Incomplete confirmations undercount; large accounts have more opportunities", "guardrails": "DB07 coverage; DB09 errors; DB13 cost", "evidence_status": "Proposed metric definition; synthetic implementation only", "baseline": null, "target": null, "query": "Q01", "metabase_status": "Reusable metric", "metric_card_id": 286, "model_id": 274 }, { "id": "DB02", "name": "Confirmed quality-use tasks", "meaning": "Separate output volume from reach", "business_decision": "Separate output volume from reach", "formula": "COUNT(confirmed_quality_use=1)", "unit": "tasks", "grain": "task", "numerator": "Accepted/no-critical-error tasks confirmed used", "denominator": "None; count", "eligible_cohort_window": "Task created cohort, use observed by cutoff", "exclusions": "Same as DB01", "data_event_source": "v_task", "owner": "Product", "leading_lagging": "lagging value", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Do not interpret a selected cohort as population prevalence.", "known_bias": "One source may spawn many locale tasks; duplicates can inflate counts", "guardrails": "DB01 account reach", "evidence_status": "Proposed metric definition; synthetic implementation only", "baseline": null, "target": null, "query": "Q01", "metabase_status": "Reusable metric", "metric_card_id": 288, "model_id": 273 }, { "id": "DB03", "name": "Task milestone counts", "meaning": "Find the next handoff to investigate", "business_decision": "Find the next handoff to investigate", "formula": "COUNT(DISTINCT task_id) at each checkpoint", "unit": "tasks", "grain": "task-checkpoint", "numerator": "Tasks with selected recorded checkpoint", "denominator": "All created tasks for context", "eligible_cohort_window": "Task created date range; events observed by cutoff", "exclusions": "No removal of blocked created tasks", "data_event_source": "v_task / sim_outputs", "owner": "Product analytics", "leading_lagging": "leading", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Do not interpret a selected cohort as population prevalence.", "known_bias": "Missing telemetry differs from abandonment; review/export parallel", "guardrails": "Q24 flow conservation", "evidence_status": "Proposed metric definition; synthetic implementation only", "baseline": null, "target": null, "query": "Q02", "metabase_status": "Reusable metric", "metric_card_id": 290, "model_id": 276 }, { "id": "DB04", "name": "Render completion rate", "meaning": "Isolate backend reliability from use", "business_decision": "Isolate backend reliability from use", "formula": "SUM(render_success)/COUNT(tasks)", "unit": "fraction", "grain": "task", "numerator": "Created tasks with >=1 successful attempt", "denominator": "All created tasks", "eligible_cohort_window": "Created cohort and cutoff", "exclusions": "None; optionally publish eligible-attempt rate separately", "data_event_source": "v_task / sim_attempts", "owner": "Engineering", "leading_lagging": "leading", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Do not interpret a selected cohort as population prevalence.", "known_bias": "Entitlement/consent blocks lower all-task rate without being defects", "guardrails": "DB02 actual use", "evidence_status": "Proposed metric definition; synthetic implementation only", "baseline": null, "target": null, "query": "Q02", "metabase_status": "Reusable metric", "metric_card_id": 292, "model_id": 273 }, { "id": "DB05", "name": "Seven-day confirmed-value activation", "meaning": "Assess onboarding", "business_decision": "Assess onboarding", "formula": "SUM(activated7)/COUNT(mature7 users)", "unit": "fraction", "grain": "user signup cohort", "numerator": "Signups with quality-confirmed use in [signup,signup+7d)", "denominator": "All signups observed >=7 complete days", "eligible_cohort_window": "Individual UTC signup window, first 7 days", "exclusions": "Exclude immature users only; include zero activity", "data_event_source": "v_user_cohort", "owner": "Product analytics", "leading_lagging": "leading for return", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Do not interpret a selected cohort as population prevalence.", "known_bias": "Review must occur before day 7; reported use is incomplete", "guardrails": "DB07/09; account interference", "evidence_status": "Proposed metric definition; synthetic implementation only", "baseline": null, "target": null, "query": "Q03", "metabase_status": "Reusable metric", "metric_card_id": 294, "model_id": 275 }, { "id": "DB06", "name": "Days 28\u201341 confirmed-value return", "meaning": "Evaluate recurring need", "business_decision": "Evaluate recurring need", "formula": "SUM(return28_41)/COUNT(mature42 users)", "unit": "fraction", "grain": "user signup cohort", "numerator": "Signups with quality-confirmed use in [signup+28d,signup+42d)", "denominator": "All signups observed >=42 complete days", "eligible_cohort_window": "Full 42-day eligibility", "exclusions": "Exclude immature only; include unactivated and zero activity", "data_event_source": "v_user_cohort", "owner": "Product analytics", "leading_lagging": "lagging", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Do not interpret a selected cohort as population prevalence.", "known_bias": "Unconditional signup return is not activated-user retention; natural job frequency varies", "guardrails": "DB07 coverage by cohort", "evidence_status": "Proposed metric definition; synthetic implementation only", "baseline": null, "target": null, "query": "Q04", "metabase_status": "Reusable metric", "metric_card_id": 296, "model_id": 275 }, { "id": "DB07", "name": "Preview review coverage", "meaning": "Decide if quality inference is trustworthy", "business_decision": "Decide if quality inference is trustworthy", "formula": "COUNT(reviewed_at)/COUNT(preview_at)", "unit": "fraction", "grain": "task", "numerator": "Previewed tasks with a review", "denominator": "All previewed tasks", "eligible_cohort_window": "Created cohort; reviews by cutoff", "exclusions": "None; reviewers only after preview in this lab", "data_event_source": "v_task", "owner": "Domain quality", "leading_lagging": "measurement guardrail", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Do not interpret a selected cohort as population prevalence.", "known_bias": "Synthetic reviews sampled; real missingness could be selective", "guardrails": "Never impute missing as rejected", "evidence_status": "Proposed metric definition; synthetic implementation only", "baseline": null, "target": null, "query": "Q06", "metabase_status": "Reusable metric", "metric_card_id": 298, "model_id": 273 }, { "id": "DB08", "name": "Reviewed acceptance", "meaning": "Choose editing or quality improvements", "business_decision": "Choose editing or quality improvements", "formula": "SUM(accepted=1)/COUNT(reviewed_at)", "unit": "fraction", "grain": "reviewed task", "numerator": "Reviewed tasks accepted", "denominator": "Reviewed tasks", "eligible_cohort_window": "Created cohort; review observed", "exclusions": "Unreviewed remain NULL", "data_event_source": "sim_reviews / v_task", "owner": "Domain quality", "leading_lagging": "leading", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Do not interpret a selected cohort as population prevalence.", "known_bias": "Selected sample, not all-task acceptance", "guardrails": "DB07 and DB09", "evidence_status": "Proposed metric definition; synthetic implementation only", "baseline": null, "target": null, "query": "Q06", "metabase_status": "Reusable metric", "metric_card_id": 300, "model_id": 273 }, { "id": "DB09", "name": "Critical content failures", "meaning": "Hold unsafe or materially incorrect output", "business_decision": "Hold unsafe or materially incorrect output", "formula": "SUM(critical_error); rate=SUM/COUNT(reviewed)", "unit": "tasks and fraction", "grain": "reviewed task", "numerator": "Reviewed tasks with critical error", "denominator": "Reviewed tasks for rate; report counts too", "eligible_cohort_window": "Review cutoff; versioned rubric", "exclusions": "Unreviewed are unknown", "data_event_source": "sim_reviews", "owner": "Domain quality", "leading_lagging": "guardrail", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Do not interpret a selected cohort as population prevalence.", "known_bias": "Zero observed does not guarantee zero risk; labels fictional", "guardrails": "Numbers/names/rights slice review", "evidence_status": "Proposed metric definition; synthetic implementation only", "baseline": null, "target": null, "query": "Q06", "metabase_status": "Reusable metric", "metric_card_id": 302, "model_id": 273 }, { "id": "DB10", "name": "Ready latency p50/p95", "meaning": "Locate slow completed journeys", "business_decision": "Locate slow completed journeys", "formula": "Nearest-rank percentile(ready_at-created_at)", "unit": "seconds", "grain": "completed task", "numerator": "Ordered elapsed seconds at ceil(p*n)", "denominator": "Completed task count n", "eligible_cohort_window": "Task creation to visible-ready; created cohort", "exclusions": "Incomplete tasks excluded from percentile, reported separately", "data_event_source": "v_task ready_seconds", "owner": "Engineering", "leading_lagging": "leading", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Do not interpret a selected cohort as population prevalence.", "known_bias": "Completer bias; not full human-review turnaround", "guardrails": "Q02 noncompletion and Q23 review wait", "evidence_status": "Proposed metric definition; synthetic implementation only", "baseline": null, "target": null, "query": "Q07", "metabase_status": "Exact percentile analysis in Q07; no pooled percentile metric", "metric_card_id": null, "model_id": null }, { "id": "DB11", "name": "Failure recovery to value", "meaning": "Choose recovery work", "business_decision": "Choose recovery work", "formula": "COUNT(failed_attempts>0 AND confirmed_quality_use)/COUNT(failed_attempts>0)", "unit": "fraction", "grain": "task", "numerator": "Tasks with failed attempt then quality-use", "denominator": "Tasks with >=1 failed attempt", "eligible_cohort_window": "By fixed cutoff; disclose recovery observation time", "exclusions": "Pre-attempt entitlement blocks are separate", "data_event_source": "v_task", "owner": "Engineering/CS", "leading_lagging": "leading", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Do not interpret a selected cohort as population prevalence.", "known_bias": "Right censoring and recoverability mix; render recovery differs", "guardrails": "DB12 repeated work; DB16 debit correctness", "evidence_status": "Proposed metric definition; synthetic implementation only", "baseline": null, "target": null, "query": "Q08", "metabase_status": "Reusable metric", "metric_card_id": 304, "model_id": 273 }, { "id": "DB12", "name": "Task retry rate", "meaning": "Diagnose repeated work", "business_decision": "Diagnose repeated work", "formula": "COUNT(attempts>1)/COUNT(attempts>0)", "unit": "fraction", "grain": "task", "numerator": "Tasks with multiple render attempts", "denominator": "Tasks with any render attempt", "eligible_cohort_window": "Created cohort", "exclusions": "Pre-attempt blocks", "data_event_source": "v_task", "owner": "Engineering", "leading_lagging": "diagnostic", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Do not interpret a selected cohort as population prevalence.", "known_bias": "Helpful retry should not be suppressed just to reduce rate", "guardrails": "DB11 and total cost", "evidence_status": "Proposed metric definition; synthetic implementation only", "baseline": null, "target": null, "query": "Q08", "metabase_status": "Reusable metric", "metric_card_id": 306, "model_id": 273 }, { "id": "DB13", "name": "Direct vendor USD per confirmed-use task", "meaning": "Choose full task improvements", "business_decision": "Choose full task improvements", "formula": "SUM(direct_vendor_usd)/SUM(confirmed_quality_use)", "unit": "USD/task", "grain": "task cohort", "numerator": "Render/translation/delivery/vendor-review/support costs across all selected tasks", "denominator": "Confirmed quality-use tasks in selected cohort", "eligible_cohort_window": "Task costs allocated to task-created month", "exclusions": "Period idle/shared excluded here; shown in DB23; customer labor separate", "data_event_source": "sim_costs preaggregated in v_task", "owner": "Product/finance", "leading_lagging": "lagging efficiency", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Do not interpret a selected cohort as population prevalence.", "known_bias": "Low coverage raises denominator uncertainty; rates illustrative", "guardrails": "DB07, DB09, DB23 full cost", "evidence_status": "Proposed metric definition; synthetic implementation only", "baseline": null, "target": null, "query": "Q09", "metabase_status": "Reusable metric", "metric_card_id": 308, "model_id": 273 }, { "id": "DB14", "name": "Customer active review and repair", "meaning": "Avoid moving work to people", "business_decision": "Avoid moving work to people", "formula": "AVG(prep_minutes),AVG(review_minutes),AVG(repair_minutes)", "unit": "minutes/task", "grain": "reviewed task", "numerator": "Sum each time category", "denominator": "Reviewed tasks", "eligible_cohort_window": "Created cohort", "exclusions": "Unreviewed unknown", "data_event_source": "sim_reviews", "owner": "Product/CS", "leading_lagging": "guardrail", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Do not interpret a selected cohort as population prevalence.", "known_bias": "Self-report and selected reviews; customer labor distinct from vendor cost", "guardrails": "Quality and elapsed time", "evidence_status": "Proposed metric definition; synthetic implementation only", "baseline": null, "target": null, "query": "Q10", "metabase_status": "Reusable metric", "metric_card_id": 310, "model_id": 277 }, { "id": "DB15", "name": "Estimated net customer time", "meaning": "Form a time-saving hypothesis", "business_decision": "Form a time-saving hypothesis", "formula": "AVG(manual_baseline_estimate-prep-review-repair)", "unit": "minutes/task", "grain": "reviewed task", "numerator": "Estimated baseline less all measured customer task work", "denominator": "Reviewed tasks", "eligible_cohort_window": "Same reviewed cohort", "exclusions": "Does not include all downstream work; unknown becomes gap", "data_event_source": "sim_reviews", "owner": "Research", "leading_lagging": "proposed outcome proxy", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Do not interpret a selected cohort as population prevalence.", "known_bias": "Invented baseline is not a counterfactual or causal savings", "guardrails": "Matched task comparison; quality parity", "evidence_status": "Proposed metric definition; synthetic implementation only", "baseline": null, "target": null, "query": "Q10", "metabase_status": "Reusable metric", "metric_card_id": 312, "model_id": 278 }, { "id": "DB16", "name": "Entitlement outstanding", "meaning": "Find double charge/hold leakage", "business_decision": "Find double charge/hold leakage", "formula": "SUM(reserved-consumed-released) per meter", "unit": "meter units", "grain": "task-meter", "numerator": "Reserved minus consumed minus released", "denominator": "None; balance by distinct meter", "eligible_cohort_window": "Closed-task ledger at cutoff", "exclusions": "Never combine dubbing minutes, generative credits and video counts", "data_event_source": "sim_entitlements", "owner": "Billing engineering", "leading_lagging": "guardrail", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Do not interpret a selected cohort as population prevalence.", "known_bias": "Simplified reservation model; not public billing implementation", "guardrails": "Duplicate and failed-job contract tests", "evidence_status": "Proposed metric definition; synthetic implementation only", "baseline": null, "target": null, "query": "Q12", "metabase_status": "Reusable metric", "metric_card_id": 314, "model_id": 279 }, { "id": "DB17", "name": "Experiment assignment validity", "meaning": "Decide if comparison supports inference", "business_decision": "Decide if comparison supports inference", "formula": "Accounts with >1 assigned variant / assigned accounts", "unit": "fraction", "grain": "account", "numerator": "Accounts exposed to mixed variants", "denominator": "Assigned accounts", "eligible_cohort_window": "Same experiment and exposure period", "exclusions": "None; diagnose before ITT calculation", "data_event_source": "sim_users variant", "owner": "Analytics", "leading_lagging": "validity guardrail", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Do not interpret a selected cohort as population prevalence.", "known_bias": "Lab intentionally uses seat assignments; Q13 reveals interference", "guardrails": "Randomize at account; no treatment conclusion here", "evidence_status": "Proposed metric definition; synthetic implementation only", "baseline": null, "target": null, "query": "Q13", "metabase_status": "Reusable metric", "metric_card_id": 316, "model_id": 280 }, { "id": "DB18", "name": "Acquisition spend per activated mature user", "meaning": "Choose a channel test", "business_decision": "Choose a channel test", "formula": "SUM(acquisition_usd)/SUM(activated7)", "unit": "USD/user", "grain": "user/channel", "numerator": "Allocated signup costs in mature42 cohort", "denominator": "Activated users within that mature42 cohort", "eligible_cohort_window": "42-day mature signups in selected signup period", "exclusions": "Immature excluded equally from spend and denominator", "data_event_source": "v_user_cohort", "owner": "Growth", "leading_lagging": "diagnostic", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Do not interpret a selected cohort as population prevalence.", "known_bias": "Not paying-account CAC, no causal channel attribution", "guardrails": "Later return and commercial conversion", "evidence_status": "Proposed metric definition; synthetic implementation only", "baseline": null, "target": null, "query": "Q14", "metabase_status": "Reusable metric", "metric_card_id": 318, "model_id": 275 }, { "id": "DB19", "name": "Mature zero-task share", "meaning": "Study never-starting customers", "business_decision": "Study never-starting customers", "formula": "COUNT(no task)/COUNT(mature42 users)", "unit": "fraction", "grain": "user", "numerator": "Mature users with no created task by cutoff", "denominator": "All mature42 users", "eligible_cohort_window": "42-day eligible signup cohort; no-task evaluated to cutoff", "exclusions": "Immature users", "data_event_source": "sim_users LEFT/EXISTS tasks", "owner": "Research", "leading_lagging": "leading", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Do not interpret a selected cohort as population prevalence.", "known_bias": "No sessions or stated intent available; cannot assign cause", "guardrails": "Interview nonstarters", "evidence_status": "Proposed metric definition; synthetic implementation only", "baseline": null, "target": null, "query": "Q16", "metabase_status": "Reusable metric", "metric_card_id": 320, "model_id": 275 }, { "id": "DB20", "name": "Closing subscription MRR", "meaning": "Review recurring commercial value", "business_decision": "Review recurring commercial value", "formula": "Opening+new+expansion-contraction-churn", "unit": "USD/month", "grain": "account-month", "numerator": "Normalized monthly subscription value", "denominator": "None; amount", "eligible_cohort_window": "Full calendar months only", "exclusions": "Usage packs, add-ons and one-off cash not modeled as MRR", "data_event_source": "sim_billing", "owner": "Finance", "leading_lagging": "lagging business", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Do not interpret a selected cohort as population prevalence.", "known_bias": "Illustrative contracts; not GAAP revenue; no reactivation in lab", "guardrails": "DB21/22 and cash separately", "evidence_status": "Proposed metric definition; synthetic implementation only", "baseline": null, "target": null, "query": "Q17", "metabase_status": "Reusable metric", "metric_card_id": 322, "model_id": 281 }, { "id": "DB21", "name": "Gross revenue retention", "meaning": "Detect existing-value loss", "business_decision": "Detect existing-value loss", "formula": "(opening-contraction-churn)/opening", "unit": "fraction", "grain": "existing account-month", "numerator": "Retained opening MRR excluding expansion", "denominator": "Opening MRR", "eligible_cohort_window": "Full calendar months; mature contract population", "exclusions": "Exclude new revenue and expansion", "data_event_source": "sim_billing", "owner": "Finance/CS", "leading_lagging": "lagging", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Do not interpret a selected cohort as population prevalence.", "known_bias": "Plan mix/concentration can conceal logo churn", "guardrails": "DB22; account churn needs further instrumentation", "evidence_status": "Proposed metric definition; synthetic implementation only", "baseline": null, "target": null, "query": "Q17", "metabase_status": "Reusable metric", "metric_card_id": 324, "model_id": 281 }, { "id": "DB22", "name": "Net revenue retention", "meaning": "Assess expansion versus losses", "business_decision": "Assess expansion versus losses", "formula": "(opening+expansion-contraction-churn)/opening", "unit": "fraction", "grain": "existing account-month", "numerator": "Existing MRR after expansion and losses", "denominator": "Opening MRR", "eligible_cohort_window": "Full calendar months", "exclusions": "Exclude new accounts", "data_event_source": "sim_billing", "owner": "Finance/CS", "leading_lagging": "lagging", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Do not interpret a selected cohort as population prevalence.", "known_bias": "Expansion can hide lost accounts", "guardrails": "DB21 and customer reasons", "evidence_status": "Proposed metric definition; synthetic implementation only", "baseline": null, "target": null, "query": "Q17", "metabase_status": "Reusable metric", "metric_card_id": 326, "model_id": 281 }, { "id": "DB23", "name": "Full period service cash contribution", "meaning": "Understand sustained service exposure", "business_decision": "Understand sustained service exposure", "formula": "net cash-payment fees-direct costs-idle/shared", "unit": "USD", "grain": "period", "numerator": "Cash contribution after declared service scope", "denominator": "None; amount, margin=amount/net cash if >0", "eligible_cohort_window": "Whole calendar months; October partial excluded by default", "exclusions": "Acquisition/R&D/corporate overhead excluded from service proxy; R&D separately shown", "data_event_source": "sim_billing + preaggregated sim_costs + sim_period_costs", "owner": "Finance", "leading_lagging": "lagging", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Do not interpret a selected cohort as population prevalence.", "known_bias": "Not accounting gross profit; acquisition needs separate reconciliation", "guardrails": "Quality, vendor and customer workload", "evidence_status": "Proposed metric definition; synthetic implementation only", "baseline": null, "target": null, "query": "Q18", "metabase_status": "Reusable metric", "metric_card_id": 328, "model_id": 282 }, { "id": "DB24", "name": "Heldout task pass by slice", "meaning": "Select a candidate without averaging harm", "business_decision": "Select a candidate without averaging harm", "formula": "SUM(task_pass)/COUNT(heldout cases)", "unit": "fraction", "grain": "case-candidate-slice", "numerator": "Candidate passing task cases", "denominator": "Same independent heldout cases per candidate", "eligible_cohort_window": "Frozen development/heldout split", "exclusions": "Development cases excluded; repeats not independent samples", "data_event_source": "sim_eval_cases/results", "owner": "AI/domain evaluation", "leading_lagging": "pre-release", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Use paired case bootstrap; no real model benchmark.", "known_bias": "Fictional labels; no media or model runs; paired comparison needed", "guardrails": "Critical failures, reviewer disagreement, latency/cost", "evidence_status": "Proposed metric definition; synthetic implementation only", "baseline": null, "target": null, "query": "Q19", "metabase_status": "Reusable metric", "metric_card_id": 330, "model_id": 283 }, { "id": "DB25", "name": "Judge failure-detection recall", "meaning": "Choose the role of automatic checks", "business_decision": "Choose the role of automatic checks", "formula": "true_failure_detected/(true_failure_detected+missed_failure)", "unit": "fraction", "grain": "heldout case-candidate", "numerator": "Human-labeled failures detected by judge", "denominator": "All human-labeled failures", "eligible_cohort_window": "Same heldout set", "exclusions": "Undefined with no failures", "data_event_source": "sim_eval_results", "owner": "Evaluation", "leading_lagging": "guardrail", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Do not interpret a selected cohort as population prevalence.", "known_bias": "Synthetic judge; errors can correlate with the same model", "guardrails": "False alarms and critical misses by slice", "evidence_status": "Proposed metric definition; synthetic implementation only", "baseline": null, "target": null, "query": "Q20", "metabase_status": "Reusable metric", "metric_card_id": 332, "model_id": 283 }, { "id": "DB26", "name": "Engineering capacity demand", "meaning": "Choose bounded scope", "business_decision": "Choose bounded scope", "formula": "SUM(eng_weeks) of selected dependent opportunities", "unit": "person-weeks", "grain": "opportunity portfolio", "numerator": "Estimated engineering person-weeks", "denominator": "None; demand; compare to available capacity after reserve", "eligible_cohort_window": "Declared planning horizon, currently unapproved", "exclusions": "No conversion to calendar deadline", "data_event_source": "plan_opportunities", "owner": "Engineering/PM", "leading_lagging": "planning input", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Do not interpret a selected cohort as population prevalence.", "known_bias": "Low/high reach is scenario range; no causal effect estimate", "guardrails": "Design/reviewer capacity and dependencies", "evidence_status": "Proposed metric definition; synthetic implementation only", "baseline": null, "target": null, "query": "Q21", "metabase_status": "Reusable metric", "metric_card_id": 334, "model_id": 284 }, { "id": "DB27", "name": "Unresolved release gates", "meaning": "Hold launch until evidence exists", "business_decision": "Hold launch until evidence exists", "formula": "COUNT(gate state != verified)", "unit": "gates", "grain": "requirement-release", "numerator": "Unverified required gates", "denominator": "All required gates for context", "eligible_cohort_window": "Exact proposed release/version", "exclusions": "Do not equate test specification with passing result", "data_event_source": "plan_gates", "owner": "Engineering/PM/domain", "leading_lagging": "release guardrail", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Do not interpret a selected cohort as population prevalence.", "known_bias": "All are unverified; synthetic labels cannot approve real release", "guardrails": "Named approvals and rollback drill", "evidence_status": "Proposed metric definition; synthetic implementation only", "baseline": null, "target": null, "query": "Q22", "metabase_status": "Reusable metric", "metric_card_id": 336, "model_id": 285 }, { "id": "DB28", "name": "Time from creation to confirmed use", "meaning": "Balance machine and human waits", "business_decision": "Balance machine and human waits", "formula": "AVG(confirmed_use_at-created_at); percentile recommended", "unit": "hours", "grain": "completed useful task", "numerator": "Elapsed hours across confirmed-quality-use tasks", "denominator": "Confirmed quality-use tasks", "eligible_cohort_window": "Created cohort to use cutoff", "exclusions": "Unconfirmed excluded, report coverage", "data_event_source": "v_task", "owner": "Product operations", "leading_lagging": "lagging", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Do not interpret a selected cohort as population prevalence.", "known_bias": "Completer bias; mean hides tail; Q23 reports review wait separately", "guardrails": "Missing-use count and active workload", "evidence_status": "Proposed metric definition; synthetic implementation only", "baseline": null, "target": null, "query": "Q23", "metabase_status": "Reusable metric", "metric_card_id": 338, "model_id": 273 }, { "id": "DB29", "name": "Eligible payment success", "meaning": "Separate payment failure from product-value failure", "business_decision": "Separate payment failure from product-value failure", "formula": "successful unique payment intents / eligible submitted payment intents", "unit": "fraction", "grain": "payment intent", "numerator": "Eligible payment intents with confirmed successful settlement", "denominator": "Unique eligible submitted intents, including failed attempts under the same intent", "eligible_cohort_window": "Declared checkout cohort and settlement lag", "exclusions": "Internal tests, duplicate transport events; cancellations reported separately", "data_event_source": "PROPOSED payment intent and provider settlement events; absent from lab", "owner": "Billing/growth", "leading_lagging": "commercial leading", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Do not interpret a selected cohort as population prevalence.", "known_bias": "Retries/events are not separate buyers; asynchronous settlement can be delayed", "guardrails": "Refunds, duplicate debits, customer value", "evidence_status": "Proposed definition; not instrumented or implemented in this lab", "baseline": null, "target": null, "query": null, "metabase_status": "Not instrumented; no fabricated values", "metric_card_id": null, "model_id": null }, { "id": "DB30", "name": "Mature account paid conversion", "meaning": "Test sustainable commercial adoption", "business_decision": "Test sustainable commercial adoption", "formula": "new accounts becoming net paying within 30 days / all new accounts observed 30 days", "unit": "fraction", "grain": "account signup cohort", "numerator": "Eligible new accounts with first settled non-refunded paid subscription in window", "denominator": "All eligible new accounts mature 30 days, including zero activity", "eligible_cohort_window": "[account creation, creation+30d), plus explicit refund-lag policy", "exclusions": "Internal/test accounts; exclude existing customers; no seat duplication", "data_event_source": "PROPOSED account signup, settlement, subscription and refund linkage; not implemented", "owner": "Growth/finance", "leading_lagging": "commercial lagging", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Do not interpret a selected cohort as population prevalence.", "known_bias": "Sales-led and self-service intent differ; invoice issue is not payment", "guardrails": "Quality use, refunds, service contribution and mature return", "evidence_status": "Proposed definition; not instrumented or implemented in this lab", "baseline": null, "target": null, "query": null, "metabase_status": "Not instrumented; no fabricated values", "metric_card_id": null, "model_id": null }, { "id": "DB31", "name": "Stale approval prevention", "meaning": "Protect current-version distribution", "business_decision": "Protect current-version distribution", "formula": "blocked stale-version distribution attempts / all stale-version distribution attempts", "unit": "fraction", "grain": "distribution attempt", "numerator": "Stale approval attempts correctly blocked by server", "denominator": "All stale approval attempts, with audited detection coverage", "eligible_cohort_window": "Release/version test suite and production audit period reported separately", "exclusions": "Do not mix synthetic test and real operational populations", "data_event_source": "PROPOSED source/target hashes, approval and final distribution events; absent from lab", "owner": "Engineering/domain", "leading_lagging": "quality guardrail", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Do not interpret a selected cohort as population prevalence.", "known_bias": "No detected attempt does not prove no stale distribution; false blocks need auditing", "guardrails": "Unauthorized distribution and reviewer burden", "evidence_status": "Proposed definition; not instrumented or implemented in this lab", "baseline": null, "target": null, "query": null, "metabase_status": "Not instrumented; no fabricated values", "metric_card_id": null, "model_id": null }, { "id": "DB32", "name": "Confirmed unauthorized disclosure", "meaning": "Keep privacy separate from usage growth", "business_decision": "Keep privacy separate from usage growth", "formula": "count of independently confirmed unauthorized content/data disclosures", "unit": "incidents", "grain": "incident", "numerator": "Confirmed incidents by severity and affected tenant", "denominator": "No rate denominator required; also report audit coverage and exposure", "eligible_cohort_window": "Declared incident detection/reporting period; revisions versioned", "exclusions": "False positives adjudicated separately; missing audit evidence unknown", "data_event_source": "PROPOSED access audit, incident and deletion evidence; absent from lab", "owner": "Security/privacy", "leading_lagging": "privacy guardrail", "uncertainty": "Real baseline/target unknown. Fictional outputs are descriptive practice; report n, coverage and slices. Do not interpret a selected cohort as population prevalence.", "known_bias": "Zero reported incidents is not proof of zero exposure; avoid invasive logging", "guardrails": "Permission canaries, consent/deletion tests and response workload", "evidence_status": "Proposed definition; not instrumented or implemented in this lab", "baseline": null, "target": null, "query": null, "metabase_status": "Not instrumented; no fabricated values", "metric_card_id": null, "model_id": null } ], "dashboard_id": 11, "state": { "models": { "task": { "id": 273, "sql": "SELECT *,CASE WHEN preview_at IS NOT NULL THEN 1 ELSE 0 END previewed,CASE WHEN preview_at IS NOT NULL AND reviewed_at IS NOT NULL THEN 1 ELSE 0 END reviewed_preview,CASE WHEN reviewed_at IS NOT NULL THEN 1 ELSE 0 END reviewed,CASE WHEN accepted=1 THEN 1 ELSE 0 END accepted_flag,CASE WHEN critical_error=1 THEN 1 ELSE 0 END critical_flag,CASE WHEN failed_attempts>0 THEN 1 ELSE 0 END had_failure,CASE WHEN failed_attempts>0 AND confirmed_quality_use=1 THEN 1 ELSE 0 END recovered_value,CASE WHEN attempts>0 THEN 1 ELSE 0 END attempted,CASE WHEN attempts>1 THEN 1 ELSE 0 END retried,CASE WHEN confirmed_use_at IS NOT NULL THEN (julianday(confirmed_use_at)-julianday(created_at))*86400 END use_seconds FROM v_task", "scope": "One row per task; attempts and vendor costs preaggregated" }, "week": { "id": 274, "sql": "SELECT account_id,task_id,persona,workflow,date(confirmed_use_at,'weekday 0','-6 days') week_start FROM v_task WHERE confirmed_quality_use=1 AND date(confirmed_use_at,'weekday 0','-6 days')>=date((SELECT MIN(signup_at) FROM sim_users)) AND date(confirmed_use_at,'weekday 0','-6 days','+7 days')<=date((SELECT value FROM manifest WHERE key='cutoff_utc'))", "scope": "One row per confirmed quality-use task; group by week" }, "cohort": { "id": 275, "sql": "SELECT *,mature7*activated7 activated_eligible,mature42*return28_41 returned_eligible,CASE WHEN mature42=1 AND NOT EXISTS(SELECT 1 FROM sim_tasks t WHERE t.user_id=c.user_id) THEN 1 ELSE 0 END zero_mature,CASE WHEN mature7=1 THEN acquisition_usd ELSE 0 END eligible_spend FROM v_user_cohort c", "scope": "One row per signup including zero-activity users" }, "milestone": { "id": 276, "sql": "SELECT task_id,persona,workflow,'created' checkpoint FROM v_task UNION ALL SELECT task_id,persona,workflow,'eligible' checkpoint FROM v_task WHERE eligible=1 UNION ALL SELECT task_id,persona,workflow,'ready' checkpoint FROM v_task WHERE ready_at IS NOT NULL UNION ALL SELECT task_id,persona,workflow,'preview' checkpoint FROM v_task WHERE preview_at IS NOT NULL UNION ALL SELECT task_id,persona,workflow,'review' checkpoint FROM v_task WHERE reviewed_at IS NOT NULL UNION ALL SELECT task_id,persona,workflow,'export' checkpoint FROM v_task WHERE exported_at IS NOT NULL UNION ALL SELECT task_id,persona,workflow,'distribution' checkpoint FROM v_task WHERE distributed_at IS NOT NULL UNION ALL SELECT task_id,persona,workflow,'confirmed use' checkpoint FROM v_task WHERE confirmed_use_at IS NOT NULL", "scope": "One task per recorded checkpoint; group by checkpoint" }, "work": { "id": 277, "sql": "SELECT task_id,persona,workflow,'prep_minutes' component,prep_minutes minutes FROM v_task WHERE reviewed_at IS NOT NULL UNION ALL SELECT task_id,persona,workflow,'review_minutes' component,review_minutes minutes FROM v_task WHERE reviewed_at IS NOT NULL UNION ALL SELECT task_id,persona,workflow,'repair_minutes' component,repair_minutes minutes FROM v_task WHERE reviewed_at IS NOT NULL", "scope": "One reviewed task per workload component; group by component" }, "estimate": { "id": 278, "sql": "SELECT *,manual_baseline_estimate_minutes-prep_minutes-review_minutes-repair_minutes estimated_net_minutes FROM v_task WHERE reviewed_at IS NOT NULL", "scope": "One reviewed task; manual baseline is an estimate" }, "meter": { "id": 279, "sql": "SELECT e.*,t.persona,t.workflow,reserved-consumed-released outstanding FROM sim_entitlements e JOIN v_task t USING(task_id)", "scope": "One entitlement per task; never combine incompatible meter units" }, "assignment": { "id": 280, "sql": "SELECT account_id,COUNT(DISTINCT variant) variants,CASE WHEN COUNT(DISTINCT variant)>1 THEN 1 ELSE 0 END mixed FROM sim_users GROUP BY account_id", "scope": "One account with assigned users; validity audit not treatment effect" }, "billing": { "id": 281, "sql": "SELECT *,opening_mrr-contraction-churn retained_base,opening_mrr+expansion-contraction-churn retained_expanded FROM sim_billing WHERE month'research_and_development' THEN cost_usd ELSE 0 END) service_allocated,SUM(CASE WHEN component='research_and_development' THEN cost_usd ELSE 0 END) rd FROM sim_period_costs GROUP BY month) SELECT b.*,COALESCE(c.direct_usd,0) direct_usd,f.service_allocated,f.rd,b.net_cash-b.payment_fee-COALESCE(c.direct_usd,0)-f.service_allocated service_cash_contribution,b.net_cash-b.payment_fee-COALESCE(c.direct_usd,0)-f.service_allocated-f.rd after_rd_cash_proxy FROM billing b LEFT JOIN costs c USING(month) JOIN fixed f USING(month) WHERE month'verified' THEN 1 ELSE 0 END unresolved FROM plan_gates", "scope": "One proposed release gate; unknown is not verified" } }, "metrics": { "DB01": { "id": 286, "source": "week", "formula": [ "distinct", [ "field", "account_id", { "base-type": "type/Float" } ] ], "sql_aggregation": "COUNT(DISTINCT account_id)", "dimension": "week_start", "rows": [ [ "2026-05-11", 1 ], [ "2026-05-18", 3 ], [ "2026-05-25", 3 ], [ "2026-06-01", 3 ], [ "2026-06-08", 3 ], [ "2026-06-15", 3 ], [ "2026-06-22", 7 ], [ "2026-06-29", 7 ], [ "2026-07-06", 8 ], [ "2026-07-13", 17 ], [ "2026-07-20", 11 ], [ "2026-07-27", 11 ], [ "2026-08-03", 14 ], [ "2026-08-10", 7 ], [ "2026-08-17", 8 ], [ "2026-08-24", 13 ], [ "2026-08-31", 10 ], [ "2026-09-07", 9 ], [ "2026-09-14", 8 ], [ "2026-09-21", 11 ], [ "2026-09-28", 10 ], [ "2026-10-05", 12 ], [ "2026-10-12", 14 ] ] }, "DB02": { "id": 288, "source": "task", "formula": [ "sum", [ "field", "confirmed_quality_use", { "base-type": "type/Float" } ] ], "sql_aggregation": "SUM(confirmed_quality_use)", "dimension": "workflow", "rows": [ [ "api_template", 89 ], [ "document_avatar", 76 ], [ "dubbing", 56 ] ] }, "DB03": { "id": 290, "source": "milestone", "formula": [ "distinct", [ "field", "task_id", { "base-type": "type/Float" } ] ], "sql_aggregation": "COUNT(DISTINCT task_id)", "dimension": "checkpoint", "rows": [ [ "confirmed use", 221 ], [ "created", 1300 ], [ "distribution", 289 ], [ "eligible", 1201 ], [ "export", 698 ], [ "preview", 903 ], [ "ready", 1042 ], [ "review", 617 ] ] }, "DB04": { "id": 292, "source": "task", "formula": [ "/", [ "sum", [ "field", "render_success", { "base-type": "type/Float" } ] ], [ "count" ] ], "sql_aggregation": "SUM(render_success)*1.0/COUNT(*)", "dimension": "workflow", "rows": [ [ "api_template", 0.8382022471910112 ], [ "document_avatar", 0.8220720720720721 ], [ "dubbing", 0.7396593673965937 ] ] }, "DB05": { "id": 294, "source": "cohort", "formula": [ "/", [ "sum", [ "field", "activated_eligible", { "base-type": "type/Float" } ] ], [ "sum", [ "field", "mature7", { "base-type": "type/Float" } ] ] ], "sql_aggregation": "SUM(activated_eligible)*1.0/NULLIF(SUM(mature7),0)", "dimension": "persona", "rows": [ [ "developer", 0.07766990291262135 ], [ "marketing", 0.0380952380952381 ], [ "training", 0.0673076923076923 ] ] }, "DB06": { "id": 296, "source": "cohort", "formula": [ "/", [ "sum", [ "field", "returned_eligible", { "base-type": "type/Float" } ] ], [ "sum", [ "field", "mature42", { "base-type": "type/Float" } ] ] ], "sql_aggregation": "SUM(returned_eligible)*1.0/NULLIF(SUM(mature42),0)", "dimension": "cohort_month", "rows": [ [ "2026-05-01", 0.09615384615384616 ], [ "2026-06-01", 0.27450980392156865 ], [ "2026-07-01", 0.125 ], [ "2026-08-01", 0.13333333333333333 ], [ "2026-09-01", 0.1 ], [ "2026-10-01", null ] ] }, "DB07": { "id": 298, "source": "task", "formula": [ "/", [ "sum", [ "field", "reviewed_preview", { "base-type": "type/Float" } ] ], [ "sum", [ "field", "previewed", { "base-type": "type/Float" } ] ] ], "sql_aggregation": "SUM(reviewed_preview)*1.0/NULLIF(SUM(previewed),0)", "dimension": "workflow", "rows": [ [ "api_template", 0.6512345679012346 ], [ "document_avatar", 0.6785714285714286 ], [ "dubbing", 0.7269372693726938 ] ] }, "DB08": { "id": 300, "source": "task", "formula": [ "/", [ "sum", [ "field", "accepted_flag", { "base-type": "type/Float" } ] ], [ "sum", [ "field", "reviewed", { "base-type": "type/Float" } ] ] ], "sql_aggregation": "SUM(accepted_flag)*1.0/NULLIF(SUM(reviewed),0)", "dimension": "workflow", "rows": [ [ "api_template", 0.8104265402843602 ], [ "document_avatar", 0.7607655502392344 ], [ "dubbing", 0.7055837563451777 ] ] }, "DB09": { "id": 302, "source": "task", "formula": [ "sum", [ "field", "critical_flag", { "base-type": "type/Float" } ] ], "sql_aggregation": "SUM(critical_flag)", "dimension": "workflow", "rows": [ [ "api_template", 10 ], [ "document_avatar", 12 ], [ "dubbing", 11 ] ] }, "DB11": { "id": 304, "source": "task", "formula": [ "/", [ "sum", [ "field", "recovered_value", { "base-type": "type/Float" } ] ], [ "sum", [ "field", "had_failure", { "base-type": "type/Float" } ] ] ], "sql_aggregation": "SUM(recovered_value)*1.0/NULLIF(SUM(had_failure),0)", "dimension": "workflow", "rows": [ [ "api_template", 0.038461538461538464 ], [ "document_avatar", 0.04838709677419355 ], [ "dubbing", 0.012658227848101266 ] ] }, "DB12": { "id": 306, "source": "task", "formula": [ "/", [ "sum", [ "field", "retried", { "base-type": "type/Float" } ] ], [ "sum", [ "field", "attempted", { "base-type": "type/Float" } ] ] ], "sql_aggregation": "SUM(retried)*1.0/NULLIF(SUM(attempted),0)", "dimension": "workflow", "rows": [ [ "api_template", 0.0364963503649635 ], [ "document_avatar", 0.02877697841726619 ], [ "dubbing", 0.03485254691689008 ] ] }, "DB13": { "id": 308, "source": "task", "formula": [ "/", [ "sum", [ "field", "direct_vendor_usd", { "base-type": "type/Float" } ] ], [ "sum", [ "field", "confirmed_quality_use", { "base-type": "type/Float" } ] ] ], "sql_aggregation": "SUM(direct_vendor_usd)*1.0/NULLIF(SUM(confirmed_quality_use),0)", "dimension": "workflow", "rows": [ [ "api_template", 15.538446876404494 ], [ "document_avatar", 16.405994684210526 ], [ "dubbing", 22.34027107142857 ] ] }, "DB14": { "id": 310, "source": "work", "formula": [ "avg", [ "field", "minutes", { "base-type": "type/Float" } ] ], "sql_aggregation": "AVG(minutes)", "dimension": "component", "rows": [ [ "prep_minutes", 7.591264181523502 ], [ "repair_minutes", 11.83679092382496 ], [ "review_minutes", 13.151458670988655 ] ] }, "DB15": { "id": 312, "source": "estimate", "formula": [ "avg", [ "field", "estimated_net_minutes", { "base-type": "type/Float" } ] ], "sql_aggregation": "AVG(estimated_net_minutes)", "dimension": "workflow", "rows": [ [ "api_template", 91.22317535545024 ], [ "document_avatar", 121.98727272727272 ], [ "dubbing", 92.78969543147208 ] ] }, "DB16": { "id": 314, "source": "meter", "formula": [ "sum", [ "field", "outstanding", { "base-type": "type/Float" } ] ], "sql_aggregation": "SUM(outstanding)", "dimension": "meter", "rows": [ [ "avatar_video_count", 0.0 ], [ "dubbing_minute", 0.0 ], [ "generative_credit", 0.0 ] ] }, "DB17": { "id": 316, "source": "assignment", "formula": [ "/", [ "sum", [ "field", "mixed", { "base-type": "type/Float" } ] ], [ "count" ] ], "sql_aggregation": "SUM(mixed)*1.0/COUNT(*)", "dimension": null, "rows": [ [ 0.23333333333333334 ] ] }, "DB18": { "id": 318, "source": "cohort", "formula": [ "/", [ "sum", [ "field", "eligible_spend", { "base-type": "type/Float" } ] ], [ "sum", [ "field", "activated_eligible", { "base-type": "type/Float" } ] ] ], "sql_aggregation": "SUM(eligible_spend)*1.0/NULLIF(SUM(activated_eligible),0)", "dimension": "channel", "rows": [ [ "partner", 1107.522 ], [ "sales", 948.9216666666666 ], [ "search", 646.80375 ] ] }, "DB19": { "id": 320, "source": "cohort", "formula": [ "/", [ "sum", [ "field", "zero_mature", { "base-type": "type/Float" } ] ], [ "sum", [ "field", "mature42", { "base-type": "type/Float" } ] ] ], "sql_aggregation": "SUM(zero_mature)*1.0/NULLIF(SUM(mature42),0)", "dimension": "persona", "rows": [ [ "developer", 0.1518987341772152 ], [ "marketing", 0.25675675675675674 ], [ "training", 0.22535211267605634 ] ] }, "DB20": { "id": 322, "source": "billing", "formula": [ "sum", [ "field", "closing_mrr", { "base-type": "type/Float" } ] ], "sql_aggregation": "SUM(closing_mrr)", "dimension": "month", "rows": [ [ "2026-05", 3840.0 ], [ "2026-06", 6991.8 ], [ "2026-07", 11277.6 ], [ "2026-08", 14592.97 ], [ "2026-09", 21453.96 ] ] }, "DB21": { "id": 324, "source": "billing", "formula": [ "/", [ "sum", [ "field", "retained_base", { "base-type": "type/Float" } ] ], [ "sum", [ "field", "opening_mrr", { "base-type": "type/Float" } ] ] ], "sql_aggregation": "SUM(retained_base)*1.0/NULLIF(SUM(opening_mrr),0)", "dimension": "month", "rows": [ [ "2026-05", null ], [ "2026-06", 0.8203125 ], [ "2026-07", 0.9193340770617009 ], [ "2026-08", 0.9827418954387458 ], [ "2026-09", 0.9551256529685185 ] ] }, "DB22": { "id": 326, "source": "billing", "formula": [ "/", [ "sum", [ "field", "retained_expanded", { "base-type": "type/Float" } ] ], [ "sum", [ "field", "opening_mrr", { "base-type": "type/Float" } ] ] ], "sql_aggregation": "SUM(retained_expanded)*1.0/NULLIF(SUM(opening_mrr),0)", "dimension": "month", "rows": [ [ "2026-05", null ], [ "2026-06", 0.823125 ], [ "2026-07", 0.94061615034755 ], [ "2026-08", 1.0314224657728595 ], [ "2026-09", 0.9592947837212027 ] ] }, "DB23": { "id": 328, "source": "period", "formula": [ "sum", [ "field", "service_cash_contribution", { "base-type": "type/Float" } ] ], "sql_aggregation": "SUM(service_cash_contribution)", "dimension": "month", "rows": [ [ "2026-05", 3152.4745359999997 ], [ "2026-06", 5896.305064 ], [ "2026-07", 9604.607195999999 ], [ "2026-08", 12676.31788 ], [ "2026-09", 19328.643828 ] ] }, "DB24": { "id": 330, "source": "eval", "formula": [ "avg", [ "field", "task_pass", { "base-type": "type/Float" } ] ], "sql_aggregation": "AVG(task_pass*1.0)", "dimension": "candidate", "rows": [ [ "baseline", 0.7962962962962963 ], [ "candidate", 0.8518518518518519 ] ] }, "DB25": { "id": 332, "source": "eval", "formula": [ "/", [ "sum", [ "field", "detected_failure", { "base-type": "type/Float" } ] ], [ "sum", [ "field", "actual_failure", { "base-type": "type/Float" } ] ] ], "sql_aggregation": "SUM(detected_failure)*1.0/NULLIF(SUM(actual_failure),0)", "dimension": "candidate", "rows": [ [ "baseline", 0.8181818181818182 ], [ "candidate", 0.8125 ] ] }, "DB26": { "id": 334, "source": "opportunity", "formula": [ "sum", [ "field", "eng_weeks", { "base-type": "type/Float" } ] ], "sql_aggregation": "SUM(eng_weeks)", "dimension": "opportunity_id", "rows": [ [ "OP1", 2.2 ], [ "OP2", 4.1 ], [ "OP3", 3.3 ], [ "OP4", 5.5 ] ] }, "DB27": { "id": 336, "source": "gate", "formula": [ "sum", [ "field", "unresolved", { "base-type": "type/Float" } ] ], "sql_aggregation": "SUM(unresolved)", "dimension": "owner_role", "rows": [ [ "Domain reviewer", 1 ], [ "Engineering", 2 ], [ "Support", 1 ] ] }, "DB28": { "id": 338, "source": "task", "formula": [ "avg", [ "field", "use_seconds", { "base-type": "type/Float" } ] ], "sql_aggregation": "AVG(use_seconds)", "dimension": "workflow", "rows": [ [ "api_template", 243038.696629981 ], [ "document_avatar", 236566.52631467502 ], [ "dubbing", 248480.66071647085 ] ] } }, "views": { "DB01": { "id": 287 }, "DB02": { "id": 289 }, "DB03": { "id": 291 }, "DB04": { "id": 293 }, "DB05": { "id": 295 }, "DB06": { "id": 297 }, "DB07": { "id": 299 }, "DB08": { "id": 301 }, "DB09": { "id": 303 }, "DB11": { "id": 305 }, "DB12": { "id": 307 }, "DB13": { "id": 309 }, "DB14": { "id": 311 }, "DB15": { "id": 313 }, "DB16": { "id": 315 }, "DB17": { "id": 317 }, "DB18": { "id": 319 }, "DB19": { "id": 321 }, "DB20": { "id": 323 }, "DB21": { "id": 325 }, "DB22": { "id": 327 }, "DB23": { "id": 329 }, "DB24": { "id": 331 }, "DB25": { "id": 333 }, "DB26": { "id": 335 }, "DB27": { "id": 337 }, "DB28": { "id": 339 }, "registry": { "id": 340 } }, "stages": { "01": 20, "02": 21, "03": 22, "04": 23, "05": 24, "06": 25, "07": 26, "08": 27 }, "source_collection": 18, "view_collection": 19, "dashboard_id": 11 } }