docs: complete run step budget slice
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@@ -54,7 +54,13 @@ validated, runnable deployment.
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7. Save and validate a deployment.
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- `wf deploy save <deployment_id> --artifact <artifact_id> --version 1 --binding <logical_source>=<concrete_source>` (or `wf deploy create` alias)
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- `wf deploy validate <deployment_id>`
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8. Run the deployment.
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8. Run the deployment with an optional step budget.
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- CLI: `wf run start <deployment_id> --input-file input.json`
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with `--max-steps 50000` (default `10_000` when omitted; at least 1)
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- Python: `await deployment.run(input, max_steps=50_000)`
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- The budget covers every frame and subgraph scope in the run. Exhaustion
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fails the run; it is never a routable workflow outcome and the denied
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handler never runs.
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9. Inspect the run summary first; read bounded traces only when needed.
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## Raw Plan Escape Hatch
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@@ -104,16 +110,19 @@ sources and choose the concrete source explicitly.
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- **Workflow capability**: graph-ready `NodeSpec` or saved wrapper artifact.
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- **Artifact**: immutable saved workflow or wrapper.
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- **Deployment**: mutable binding from artifact version to concrete sources.
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- **Run**: durable stopped execution record with status, output, and trace count.
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- **Run**: durable stopped execution record with status, output, trace count,
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and step budget (`max_steps`, `steps_executed`, `steps_remaining`).
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## Result Handling
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`wf run start` returns compact status by default. Capture `run_id` even for
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completed or failed runs. Use:
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completed or failed runs. Inspection exposes the effective budget stored
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with the run (`max_steps`, `steps_executed`, `steps_remaining`). Use:
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- `wf run inspect <run_id>` for compact stored result.
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- `wf run trace <run_id> --from 0 --limit 25` for explicit debug slices.
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- `wf run resume <run_id>` only for interrupted runs.
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- `wf run resume <run_id>` only for interrupted runs. Resume reuses the
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persisted budget and accepts no replacement value.
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Do not ask for unbounded traces.
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