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chini-train-train-0179-dp5-adversarial

Rate-Limited Search Under Enumeration Attack

brutal adversarial problem: rate-limited search under enumeration attack

Source: chini-train synth generator v0.1

Prompt

Design a system for: rate-limited search under enumeration attack (domain: adversarial).

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: $332 USD. Required behaviors: ratelimit, 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
12
Required behaviors
ratelimit, queue, circuitbreaker, retry
Monthly budget
$332

Stress scenarios

Baseline traffic

baseline

Steady ambient load with no failures.

Traffic spike

spike

Traffic suddenly multiplies. The hot path must hold.

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
78
Max drop rate
7.3%
Min delivery rate
88.0%
Max errors
5

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-0179-dp5-adversarial \
  --provider openrouter --model google/gemini-2.0-flash-001 \
  --as alice
Or inspect the prompt first:
chini-bench prompt chini-train-train-0179-dp5-adversarial
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
73 61.0 48.0 100.0
#2 rl_v07_full_a10
rl_policy
custom single-shot
73 60.0 46.0 100.0
#3 rl_v07_full_a10
rl_policy
custom single-shot
73 61.0 47.0 100.0
#4 rl_v07_full_a10
rl_policy
custom single-shot
73 61.0 47.0 100.0
#5 chini-train-03
grok-4.1-fast
single-shot
65 49.0 30.0 100.0
#6 chini-train-04
grok-4.1-fast
single-shot
65 49.0 30.0 100.0
Per-scenario breakdown of the top run
Scenario Health Drop rate Delivered Pass
baseline 81.0 1.7% 29
spike-1 63.0 14.5% 1254
outage-2 71.0 2.8% 0
cascade-3 28.0 67.4% 7