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Arquitecto de Soluciones Principal y Consultor Tecnológico de Andru.ia. Diagnostica y traza la hoja de ruta óptima para proyectos de IA en español.
Use when an agent workflow needs deterministic recovery evidence for sandbox, MCP/tool, worker, checkpoint, memory, or orchestration failures.
$ npx -y skills add sickn33/agentic-awesome-skills --skill agent-harness-fault-injection --agent claude-codeHow it fires
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/agent-harness-fault-injectionContext preview
The summary Claude sees to decide when to auto-load this skill.
Use when an agent workflow needs deterministic recovery evidence for sandbox, MCP/tool, worker, checkpoint, memory, or orchestration failures.
name: agent-harness-fault-injection description: "Use when an agent workflow needs deterministic recovery evidence for sandbox, MCP/tool, worker, checkpoint, memory, or orchestration failures." category: development risk: safe source: self source_type: self date_added: "2026-08-19" author: Whxuan0701 tags: [agent-harness, fault-injection, recovery, state-machine, mcp, multi-agent] tools: [claude, cursor, gemini, codex-cli]
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.
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.
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 process, or mutate a live service to create a failure. 4. Record the test scope and a run identifier before starting. A missing scope, fixture, or recovery contract makes the verdict `inconclusive`.
Write the invariant before injecting a fault. A useful contract names the state that must survive and the side effects that must not repeat:
After recovery, resume from the latest durable checkpoint, preserve the task identity and safety policy, spend no more than the remaining retry/deadline budget, and commit each externally visible effect at most once.
Model the workflow with explicit states. For example:
created -> running -> checkpointed -> waiting_for_tool
| |
v v
failed <--------- recovering -> resumed -> completedFor each transition, define the owner, durable fields, allowed retry count, and terminal behavior. In-memory values are not checkpoints unless the harness proves they survive the simulated restart.
Select the smallest set of faults that covers the new recovery logic. Do not randomize the schedule until a deterministic schedule has passed.
| Fault | Injection boundary | Required observation | Expected containment | |---|---|---|---| | sandbox denial | before a tool starts | no unsafe side effect; reason is retained | retry only when policy allows | | MCP/tool timeout | after request id is assigned | timeout is attributed to that request | bounded retry with same idempotency key | | worker restart | after checkpoint write | worker reloads the same task version | resume from latest checkpoint | | missing/stale checkpoint | before resume | stale data is rejected or marked | stop safely; never invent progress | | parallel branch failure | one branch after fan-out | sibling status is preserved | join policy decides retry, degrade, or stop | | memory loss | clear ephemeral context | durable facts are reconstructed | ask or stop when required facts are absent | | retry/deadline exhaustion | on the final attempt | no extra call is scheduled | terminal `failed` or `timed_out` |
Use event numbers rather than wall-clock randomness. A schedule should be portable across harnesses:
{
"seed": "harness-fixture-07",
"faults": [
{"event": "tool.call", "ordinal": 2, "kind": "timeout", "tool": "search"},
{"event": "worker.start", "ordinal": 2, "kind": "restart"},
{"event": "branch.join", "ordinal": 1, "kind": "partial_failure", "branch": "summarize"}
]
}The harness should emit the schedule, not merely the seed. Keep fault identity separate from the observed error so a wrapper cannot accidentally turn a timeout into a generic failure. Run the same schedule twice and compare the normalized timeline before trying a different schedule.
attempt count in the evidence.
replay. A read timeout is not proof that a write did not happen.
stop scheduling work.
budgets, and the checkpoint sequence before a restart test.
checkpoint instead of guessing.
cannot be proven, downgrade the verdict and require reconciliation.
Represent each branch as its own child attempt. The join record must retain success, failure, timeout, and not-started states.
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Repo: sickn33/agentic-awesome-skills
Arquitecto de Soluciones Principal y Consultor Tecnológico de Andru.ia. Diagnostica y traza la hoja de ruta óptima para proyectos de IA en español.
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