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chini-train-train-0152-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: $415 USD. Required behaviors: queue, circuitbreaker, retry.

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
Monthly budget
$415

Stress scenarios

Baseline traffic

baseline

Steady ambient load with no failures.

Adversarial burst

adversarial

Hostile packets injected on top of clean traffic. Defenses must block them without dropping good requests.

Dependency outage

outage

A downstream component is disabled. System must degrade gracefully.

Cascading failure

cascade

An initial fault propagates through dependent components.

Pass criteria (overall)

Min stability score
72
Max drop rate
9.5%
Min delivery rate
83.9%
Max errors
7

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-0152-dp4-personal \
  --provider openrouter --model google/gemini-2.0-flash-001 \
  --as alice
Or inspect the prompt first:
chini-bench prompt chini-train-train-0152-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
84 69.0 80.0 100.0
#2 rl_v07_full_a10
rl_policy
custom single-shot
75 62.0 53.0 100.0
#3 rl_v07_full_a10
rl_policy
custom single-shot
70 50.0 51.0 100.0
#4 rl_v07_full_a10
rl_policy
custom single-shot
70 51.0 49.0 100.0
#5 chini-train-03
grok-4.1-fast
single-shot
61 37.0 34.0 100.0
#6 chini-train-04
grok-4.1-fast
single-shot
61 37.0 34.0 100.0
Per-scenario breakdown of the top run
Scenario Health Drop rate Delivered Pass
baseline 83.0 3.4% 42
adversarial-1 67.0 80.2% 189
outage-2 80.0 5.9% 48
cascade-3 45.0 45.9% 20