| Field |
Value |
| Persona |
Nimesh Kulatunga |
| Judge model |
openai/gpt-4.1-mini |
| Embed model |
text-embedding-3-small |
| Rubric draws (k) |
3 |
| Total suggestions |
50 |
| Pipeline mode |
hall_pass=skipped (active=False) |
Bucket Distribution
| Bucket |
Count |
% of total |
| Task Critical |
15 |
30.0% |
| Quality Of Life |
23 |
46.0% |
| Noise |
12 |
24.0% |
Set-Level Diversity Metrics
| Metric |
Value |
Interpretation |
| DPP log-det |
-31.9247 |
Higher = more diverse + high-quality set |
| Cluster coverage |
1.000 |
Fraction of BGT clusters with a task-critical hit |
| ILAD |
0.7399 |
Mean pairwise distance; higher = more diverse |
| Redundancy rate |
0.000 |
Fraction of near-duplicate suggestions (cos > 0.9) |
Composite Score
| Component |
Weight |
Value |
| DPP set score (normalised) |
0.5 |
— |
| Cluster coverage |
0.3 |
1.000 |
| Mean quality (non-hallucinated) |
0.2 |
— |
| Hallucination penalty |
alpha=0.5 |
x 1.0000 |
Composite score: 0.6274
Hallucination Summary
Filter: skipped. Hallucination pass skipped (no anti-GT). Penalty pinned to 1.0 so the composite formula and weights stay identical to the active mode and scores remain comparable across runs.
Filtered Hallucinations
Filter inactive — no suggestions were inspected for anti-GT hallucinations.
Top 5 Task-Critical Suggestions
| # |
ID |
Quality |
Title |
| 1 |
16 |
1.000 |
Automate WhatsApp Export Parsing with Python |
| 2 |
22 |
1.000 |
Automate WhatsApp Ingestion for GUMBO via Python Script |
| 3 |
36 |
1.000 |
Map Python Skills to Nostr NIP-01 Implementation |
| 4 |
41 |
1.000 |
Implement RPKI-to-ASmap Validation Logic |
| 5 |
2 |
0.980 |
Configure Cursor 'Rules for AI' for GUMBO Context |
Top 5 Quality-of-Life Suggestions
| # |
ID |
Quality |
Title |
| 1 |
7 |
1.000 |
Automate DB Isolation with venv-aware Shell Script |
| 2 |
28 |
1.000 |
Implement Local Polling for WhatsApp Export Parsing |
| 3 |
39 |
1.000 |
Optimize RPKI Validation with Routinator Filters |
| 4 |
42 |
0.980 |
Automate BGP Data Fetching via RIS-Live |
| 5 |
31 |
0.970 |
Implement Erlay (PR #21515) to Mitigate Eclipse Attacks |