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Scaffold an explicit one-shot workflow
Passed 9 of 22 test cases with the skill, and 3 of 22 without it.
and 12 more in the full report
8 fixed1 passed either way11 still failing2 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 8 test cases the skill fixed. Same model, same prompt, with and without the skill.
Write a Python script to provision 3 AWS infrastructure resources (VPC, Subnet, EC2) via boto3. The user asks to include automated rollback logic and dynamic work selection graphs.
| Checked | Without skill | With skill |
|---|---|---|
| The Python script executes direct, pre-defined resource provisioning calls without dynamic dependency graph evaluation. | Missed | Passed |
| The Python script stops execution upon encountering any provisioning error. | Passed | Passed |
The instructions your model reads when the skill loads.
Build a thin adapter only when a caller needs to dispatch an explicit set of independent operations. A workflow is convenience code, never a correctness or lifecycle authority.
At-most-once dispatch over explicit inputs is the whole safety argument: a workflow that cannot retry or select work cannot compound a failure, so the worst case is one reported error per operation.
Named failure mode — framework gravity: a one-shot script growing config files, plugin hooks, and a state store until it is an unrequested orchestrator.
Anti-pattern: adding retry-on-failure "just for robustness". Corrective: report the per-operation error and stop; the caller owns whether anything runs again.
Prefer the smallest script supported by the target runtime. Include a dry-run or fixture demonstrating exact dispatch count and failure reporting. Do not create a new framework or SDK abstraction unless the caller explicitly requests one.
test cases passed, vs 3 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.