chini-train-train-0352-dp4-personal
Morning Routine When Alarm Fails
hard personal problem: morning routine when alarm fails
Source: chini-train synth generator v0.1
Prompt
Design a system for: morning routine when alarm fails (domain: personal systems / habits). Tier DP4 (hard). 7-10 nodes, three stress scenarios including adversarial, tight criteria. Constraints: - At most 11 components on the canvas. - Monthly cost ceiling: $366 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
- 11
- Required behaviors
- queue, circuitbreaker, retry, ratelimit
- Monthly budget
- $366
Stress scenarios
Baseline traffic
baselineSteady ambient load with no failures.
Cascading failure
cascadeAn initial fault propagates through dependent components.
Latency injection
latencyExtra latency injected into a critical component. Tests degradation behavior under slow downstreams.
Dependency outage
outageA downstream component is disabled. System must degrade gracefully.
Pass criteria (overall)
- Min stability score
- 79
- Max drop rate
- 8.8%
- Min delivery rate
- 87.5%
- Max errors
- 6
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-0352-dp4-personal \
--provider openrouter --model google/gemini-2.0-flash-001 \
--as alice Or inspect the prompt first:
chini-bench prompt chini-train-train-0352-dp4-personal 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 | 87 | 70.0 | 78.0 | 100.0 | ✗ |
| #2 | rl_v07_full_a10 | rl_policy custom single-shot | 86 | 68.0 | 74.0 | 100.0 | ✗ |
| #3 | rl_v07_full_a10 | rl_policy custom single-shot | 80 | 66.0 | 48.0 | 100.0 | ✗ |
| #4 | chini-train-03 | grok-4.1-fast single-shot | 74 | 47.0 | 42.0 | 100.0 | ✗ |
| #5 | chini-train-04 | grok-4.1-fast single-shot | 74 | 47.0 | 42.0 | 100.0 | ✗ |
| #6 | rl_v07_full_a10 | rl_policy custom single-shot | 64 | 50.0 | 30.0 | 85.0 | ✗ |
Per-scenario breakdown of the top run
| Scenario | Health | Drop rate | Delivered | Pass |
|---|---|---|---|---|
| baseline | 81.0 | 3.4% | 28 | ✓ |
| cascade-1 | 35.0 | 56.5% | 10 | ✗ |
| latency-2 | 81.0 | 2.9% | 34 | ✓ |
| outage-3 | 81.0 | 2.9% | 34 | ✓ |