agent-harness-fault-injection

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Use when an agent workflow needs deterministic recovery evidence for sandbox, MCP/tool, worker, checkpoint, memory, or orchestration failures.

AI & Automation 46,271 stars 6746 forks Updated 2 days ago MIT

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# Agent Harness Fault Injection ## Overview Use a deterministic, non-production fault schedule to test whether an agent workflow preserves state, budgets, safety boundaries, and evidence when a dependency fails. The output is a small fault matrix, an event timeline, and a verdict that distinguishes recovered, contained, unrecoverable, and inconclusive runs. ## When to Use This Skill - Use when a multi-step agent, state machine, loop, or multi-agent workflow has a new recovery path. - Use when sandbox execution, an MCP/tool call, a worker, a checkpoint store, or memory can time out or disappear. - Use before claiming retry, resume, deadline, isolation, or partial-failure behavior is production-ready. - Use when a regression needs reproducible failure evidence instead of a random chaos run. Do not use this skill against a production target, real user data, live credentials, or an unbounded external service. Convert those cases to a local simulator or an authorized staging harness first. ## Safety and Boundary Preconditions 1. Freeze the workflow revision, model/prompt configuration, tool schemas, seed, input fixture, timeout, retry budget, deadline, and expected terminal states. 2. Run in a disposable sandbox with synthetic inputs and stubbed tools. Keep network disabled unless the test explicitly needs a local test server. 3. Make every injected failure an in-memory or fixture-controlled event. Never delete real data, revoke real credentials, kill an unrelated ...

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Author
sickn33
Repository
sickn33/agentic-awesome-skills
Created
7 months ago
Last Updated
2 days ago
Language
Python
License
MIT

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