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EvalMonkey debuts local agent chaos testing

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EvalMonkey debuts local agent chaos testing
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// 45d agoOPENSOURCE RELEASE

EvalMonkey debuts local agent chaos testing

EvalMonkey is a strictly local, open-source framework for benchmarking AI agents against 10 HuggingFace datasets and then stress-testing them with chaos profiles like schema errors, latency spikes, rate limits, context overflow, and prompt injection. It supports custom agent endpoints and BYO model providers including OpenAI, Ollama, Bedrock, Azure, and GCP.

// ANALYSIS

This is useful because it measures the failure mode most evals ignore: how much an agent degrades once the happy path stops being clean. The local-only design removes the biggest adoption blocker for teams that do not want to send eval traffic to a third-party service. Pairing a capability score with a resilience score is more actionable than a single benchmark number, especially for tool-using agents. The chaos profiles map to real production failures, which makes this relevant for orchestration, middleware, and agent reliability work. The maintainer-wanted framing suggests the project is early, but the problem it targets is real and under-served.

// TAGS
evalmonkeyagenttestingbenchmarkautomationopen-sourceself-hosted

DISCOVERED

45d ago

2026-04-17

PUBLISHED

45d ago

2026-04-17

RELEVANCE

8/ 10

AUTHOR

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