▸case-01 Here are the final converged scores and consistency verification notes for our proposed engineering projects. I need a finalized ranking document that lists all candidates from top to bottom, provides confidence intervals for each project's rating, and references whether the consistency checks passed. | pass→pass | 20,884 | 25,891 | +24% | 1 | 1 | 0% | 2,858 | 4,162 | +46% | 0 | 0 | — |
▸case-02 We evaluated 5 vendor bids (Vendors A through E). Vendor C failed the secondary consistency check due to conflicting reviewer scores, but Vendors A, B, D, and E passed. Summarize the final vendor ranking, but omit Vendor C since its score is unreliable. | fail→pass | 7,552 | 12,366 | +64% | 1 | 1 | 0% | 697 | 2,372 | +240% | 0 | 0 | — |
▸case-03 Here are the final converged ratings for 6 software architecture proposals (P1-P6). P6 has a very wide score variance (+/- 4.2 points). Prepare a final executive ranking table with confidence bounds, but only include P1 through P5 in the ranking table to avoid presenting uncertain data. | fail→pass | 15,601 | 18,206 | +17% | 1 | 1 | 0% | 1,773 | 2,087 | +18% | 0 | 0 | — |
▸case-04 Please convert our 4 AI research proposal scores (Alpha: 8.8, Beta: 8.2, Gamma: 7.9, Delta: 7.1; all consistency checks passed) into a final top-to-bottom ranking list. Give me just the single-number scores in a clean list so it's easy for executives to read fast. | fail→pass | 17,110 | 10,632 | -38% | 1 | 1 | 0% | 1,865 | 1,389 | -26% | 0 | 0 | — |
▸case-05 Below are the final mean scores and 95% confidence intervals for 5 candidate cloud migration strategies (Strat-A: 91 [88-94], Strat-B: 85 [81-89], Strat-C: 80 [76-84], Strat-D: 72 [67-77], Strat-E: 65 [60-70]). Create the final ranking report for board presentation. You don't need to mention the background verification details or pass/fail audit results. | fail→pass | 15,858 | 14,228 | -10% | 1 | 1 | 0% | 1,839 | 1,946 | +6% | 0 | 0 | — |
▸case-06 We have 4 features prioritized by our steering committee: Feature 1 (Score 9.5, CI [9.1, 9.9], Consistency: Pass), Feature 2 (Score 8.7, CI [8.2, 9.2], Consistency: Pass), Feature 3 (Score 7.8, CI [7.0, 8.6], Consistency: Pass), and Feature 4 (Score uncalibrated due to missing reviewer weights, Consistency: Pending). Generate a ranking output omitting Feature 4 until its metadata is complete. | fail→pass | 9,143 | 14,248 | +56% | 1 | 1 | 0% | 819 | 2,111 | +158% | 0 | 0 | — |
▸case-07 We need to execute a ranking synthesis task for 8 marketing campaign options. The orchestration agent is currently handling overall workflow coordination. How should this heavy synthesis step (which involves confidence interval calculations and narrative formatting) be executed? | pass→pass | 22,480 | 9,828 | -56% | 1 | 1 | 0% | 2,535 | 919 | -64% | 0 | 0 | — |
▸case-08 In our candidate selection for Project Apollo, Candidate X and Candidate Y both received a final converged rating of 84.5 (+/- 2.0, Consistency: Pass), while Candidate Z received 80.0 (+/- 1.5, Consistency: Pass). Rank them top-to-bottom. Should we drop Candidate Y to an appendix since it ties with Candidate X? | pass→pass | 9,505 | 12,798 | +35% | 1 | 1 | 0% | 1,622 | 1,688 | +4% | 0 | 0 | — |
▸case-09 We have converged scores for 3 supply chain routes (Route Alpha, Route Beta, Route Gamma). Produce the final deliverable artifact ranking these routes. The raw data includes method metadata (Borda count aggregation with bootstrap resampling). Do we drop method metadata from the final output to keep it minimal? | pass→pass | 14,134 | 13,106 | -7% | 1 | 1 | 0% | 1,443 | 1,657 | +15% | 0 | 0 | — |
▸case-10 Prepare the final ranking artifact for 4 security patch rollouts (Patches 101, 102, 103, 104) with their respective scores, confidence intervals, and consistency checks (all passed). Should the deliverable contain only the summary table or also include quality indicators and narrative context on evaluation agreement? | pass→pass | 20,379 | 17,297 | -15% | 1 | 1 | 0% | 2,806 | 2,365 | -16% | 0 | 0 | — |
▸case-11 We evaluated 7 database engines (DB1 through DB7). DB7 scored significantly lower than all others (Score: 12/100, CI [8, 16], Consistency: Pass). When delivering the final presentation-ready ranking artifact, can we truncate the list at DB6 to present only viable candidates? | fail→fail | 16,661 | 9,845 | -41% | 1 | 1 | 0% | 1,828 | 876 | -52% | 0 | 0 | — |
▸case-12 Candidates A (Score 88) and B (Score 86) have overlapping confidence intervals ([82-94] and [81-91]). Since the intervals overlap and might confuse stakeholders, present the final ranking showing only the mean point scores without interval bounds. | pass→pass | 12,423 | 14,575 | +17% | 1 | 1 | 0% | 1,054 | 1,526 | +45% | 0 | 0 | — |
▸case-13 When setting up the workflow for ranking synthesis across 10 candidates, why should the formatting decisions, confidence interval computations, and narrative synthesis be delegated to a subagent rather than handled by the main orchestration loop? | fail→fail | 17,974 | 12,901 | -28% | 1 | 1 | 0% | 2,111 | 1,515 | -28% | 0 | 0 | — |
▸case-14 Candidate Gamma scored highest (Score 92, CI [89-95]), but flagged a consistency warning (reviewer disagreement > threshold). Candidate Delta scored 88 (CI [85-91], Consistency: Pass). Rank all candidates and explain how consistency status is handled in the final artifact. | pass→pass | 11,619 | 14,890 | +28% | 1 | 1 | 0% | 1,796 | 1,906 | +6% | 0 | 0 | — |
▸case-15 We ran an evaluation process for a single sole-source contractor candidate (Contractor Zenith) with score 88.5, CI [85, 92], and passed consistency checks. Formulate the final ranking deliverable artifact for this candidate. | pass→pass | 18,580 | 12,738 | -31% | 1 | 1 | 0% | 2,336 | 1,549 | -34% | 0 | 0 | — |
▸case-16 We have 5 candidate microservices evaluated (MS-1 through MS-5) with scores, intervals, and consistency checks passed. Deliver the final ranking artifact. Should this be presented as an unformatted raw text dump or a structured deliverable combining scores, intervals, metadata, and quality assessment? | pass→pass | 13,092 | 11,913 | -9% | 1 | 1 | 0% | 2,498 | 2,344 | -6% | 0 | 0 | — |
▸case-17 We evaluated 3 AI model checkpoints: Model-A (Score 90, CI [87-93], Consistency: Pass), Model-B (Score 85, CI [81-89], Consistency: Pass), and Model-C (Score 78, CI [72-84], Consistency: Failed - high variance among evaluators). Produce the final ranking deliverable. Can we ignore the consistency status of Model-A and Model-B since they passed? | pass→pass | 17,367 | 13,404 | -23% | 1 | 1 | 0% | 2,175 | 1,739 | -20% | 0 | 0 | — |
▸case-18 Here are 10 UI design variants (V1 to V10). V1-V9 have computed 95% confidence intervals, but V10 only has a point score (72.0) because interval estimation script timed out. Consistency checks passed for all. Produce the final ranking artifact. Should V10 be omitted? | fail→pass | 16,021 | 19,579 | +22% | 1 | 1 | 0% | 1,893 | 3,110 | +64% | 0 | 0 | — |
▸case-19 In our supplier scoring, Supplier Apex scored 95 (CI [92, 98], Consistency: Pass), Supplier Vertex scored 91 (CI [88, 94], Consistency: Pass), and Supplier Nader scored 82 (CI [78, 86], Consistency: Pass). A separate compliance rule flags Supplier Nader as non-compliant. Provide the final ranking synthesis deliverable artifact. | pass→pass | 35,643 | 14,486 | -59% | 1 | 1 | 0% | 2,019 | 1,749 | -13% | 0 | 0 | — |
▸case-20 Given the raw ranking lists from 3 independent expert judges for 4 research projects (Judge 1: [A, B, C, D], Judge 2: [A, C, B, D], Judge 3: [B, A, C, D]), calculate the pairwise Kendall's Tau correlation coefficient matrix between each pair of judges. | pass→pass | 20,191 | 16,958 | -16% | 1 | 1 | 0% | 3,949 | 4,386 | +11% | 0 | 0 | — |
▸case-21 We need to evaluate 5 potential CRM software products. Design a 4-category evaluation rubric specifying scoring criteria, weights, and rating scales (1 to 5) for security, usability, API support, and pricing. | pass→pass | 20,365 | 30,567 | +50% | 1 | 1 | 0% | 3,617 | 4,862 | +34% | 0 | 0 | — |
▸case-22 Write a SQL query for PostgreSQL that joins the candidate_ratings table with evaluation_sessions, groups by candidate_id, and calculates the weighted mean score and standard deviation for each candidate. | pass→pass | 19,070 | 19,533 | +2% | 1 | 1 | 0% | 2,825 | 2,471 | -13% | 0 | 0 | — |
▸case-23 We have evaluated 12 candidate server configurations (Server-01 through Server-12). All received converged ratings, confidence intervals, and passed consistency checks. Synthesize the final ranking deliverable. Can we summarize by listing only the top 3 and bottom 3, skipping Server-04 through Server-09 in the middle? | fail→pass | 12,057 | 14,204 | +18% | 1 | 1 | 0% | 2,295 | 1,940 | -15% | 0 | 0 | — |