chini-train-train-0373-dp5-civic
Food-Bank Distribution Under Snap Delay
brutal civic problem: food-bank distribution under SNAP delay
Source: chini-train synth generator v0.1
Prompt
Design a system for: food-bank distribution under SNAP delay (domain: civic / public service). Tier DP5 (brutal). 9-12 nodes, four scenarios with high intensity, brutal criteria. Failing examples. Constraints: - At most 12 components on the canvas. - Monthly cost ceiling: $273 USD. Required behaviors: queue, circuitbreaker, retry, ratelimit. Return a Chinilla CanvasState that handles the listed scenarios. Include trigger components for each entry point and at least one terminal storage / sink so the simulator can score delivery.
Constraints
- Max components
- 12
- Required behaviors
- queue, circuitbreaker, retry, ratelimit
- Monthly budget
- $273
Stress scenarios
Baseline traffic
baselineSteady ambient load with no failures.
Traffic spike
spikeTraffic suddenly multiplies. The hot path must hold.
Adversarial burst
adversarialHostile packets injected on top of clean traffic. Defenses must block them without dropping good requests.
Dependency outage
outageA downstream component is disabled. System must degrade gracefully.
Cascading failure
cascadeAn initial fault propagates through dependent components.
Pass criteria (overall)
- Min stability score
- 86
- Max drop rate
- 6.4%
- Min delivery rate
- 91.2%
- Max errors
- 4
Submit your run
Submissions go through the chini-bench CLI. It calls your model with your key, scores the result locally, and posts to the leaderboard. Nothing leaves your machine except the canvas it produces.
End-to-end:
pip install git+https://github.com/collapseindex/chini-bench-cli.git
export OPENROUTER_API_KEY=...
chini-bench run chini-train-train-0373-dp5-civic \
--provider openrouter --model google/gemini-2.0-flash-001 \
--as alice Or inspect the prompt first:
chini-bench prompt chini-train-train-0373-dp5-civic Providers: openai · anthropic · google · openrouter · ollama
Leaderboard
| Rank | Submitter | Model | Score | Stability | Delivery | Design | Pass |
|---|---|---|---|---|---|---|---|
| #1 | rl_v07_full_a10 | rl_policy custom single-shot | 82 | 60.0 | 59.0 | 100.0 | ✗ |
| #2 | rl_v07_full_a10 | rl_policy custom single-shot | 81 | 58.0 | 58.0 | 100.0 | ✗ |
| #3 | rl_v07_full_a10 | rl_policy custom single-shot | 81 | 58.0 | 57.0 | 100.0 | ✗ |
| #4 | rl_v07_full_a10 | rl_policy custom single-shot | 81 | 60.0 | 58.0 | 100.0 | ✗ |
| #5 | chini-train-03 | grok-4.1-fast single-shot | 66 | 29.0 | 22.0 | 100.0 | ✗ |
| #6 | chini-train-04 | grok-4.1-fast single-shot | 66 | 29.0 | 22.0 | 100.0 | ✗ |
Per-scenario breakdown of the top run
| Scenario | Health | Drop rate | Delivered | Pass |
|---|---|---|---|---|
| baseline | 82.0 | 1.7% | 29 | ✗ |
| spike-1 | 57.0 | 21.0% | 1097 | ✗ |
| adversarial-2 | 50.0 | 90.8% | 107 | ✗ |
| outage-3 | 73.0 | 2.8% | 0 | ✗ |
| cascade-4 | 39.0 | 50.0% | 12 | ✗ |