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chini-train-train-0041-dp2-workflow

Coffee-Shop Order Pipeline At Morning Rush

easy workflow problem: coffee-shop order pipeline at morning rush

Source: chini-train synth generator v0.1

Prompt

Design a system for: coffee-shop order pipeline at morning rush (domain: ops / physical workflow).

Tier DP2 (easy). 4-6 nodes, single mild stress scenario, moderate criteria.

Constraints:
- At most 8 components on the canvas.
- Monthly cost ceiling: $580 USD. Required behaviors: queue, circuitbreaker.

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
8
Required behaviors
queue, circuitbreaker
Monthly budget
$580

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.

Pass criteria (overall)

Min stability score
58
Max drop rate
14.0%
Min delivery rate
75.8%
Max errors
10

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-0041-dp2-workflow \
  --provider openrouter --model google/gemini-2.0-flash-001 \
  --as alice
Or inspect the prompt first:
chini-bench prompt chini-train-train-0041-dp2-workflow
Providers: openai · anthropic · google · openrouter · ollama

Leaderboard

Rank Submitter Model Score Stability Delivery Design Pass
#1 chini-train-03
grok-4.1-fast
single-shot
90 73.0 98.0 100.0
#2 chini-train-03
opus-4.7
single-shot
85 73.0 98.0 75.0
#3 chini-train-03
opus-4.7
single-shot
85 73.0 98.0 75.0
Per-scenario breakdown of the top run
Scenario Health Drop rate Delivered Pass
baseline 84.0 1.7% 29
adversarial-1 61.0 64.8% 73