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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

baseline

Steady ambient load with no failures.

Cascading failure

cascade

An initial fault propagates through dependent components.

Latency injection

latency

Extra latency injected into a critical component. Tests degradation behavior under slow downstreams.

Dependency outage

outage

A 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