skills
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# Workflow Lifecycle Reference
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Use this when an agent needs to go from available capabilities to a saved,
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validated, runnable deployment.
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## Primary Path
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1. List sources.
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- MCP: `wf.admin.list_sources`
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- CLI: `wf cap list --format ids`
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2. List workflow capabilities.
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- MCP: `wf.workflow.list_capabilities`
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- CLI: `wf cap list`
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3. Inspect one capability.
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- MCP: `wf.workflow.inspect_capability`
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- CLI: `wf cap inspect <name>`
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4. Bootstrap a draft workspace.
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- MCP: `wf.workflow.create_draft_workspace_from_capability`
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- CLI: `wf draft create-from-capability <workspace_id> <capability>`
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5. Inspect/patch/validate the workspace until valid.
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- Prefer focused helpers when available.
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- Use JSON Patch only for general edits.
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6. Save an artifact.
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- Full workflow: `create_artifact_from_workspace`
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- Reusable wrapper: `create_wrapper_from_workspace`
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7. Save and validate a deployment.
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8. Run the deployment.
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9. Inspect the run summary first; read bounded traces only when needed.
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## Object Model
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- **Source**: owner of capabilities, such as `wf.std` or `everything.default`.
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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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## Result Handling
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`run_deployment` returns compact status by default. Capture `run_id` even for
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completed or failed runs. Use:
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- `inspect_run` for compact stored result.
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- `read_run_trace` for explicit debug slices, for example
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`{"start": 0, "limit": 25}`.
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- `resume_run` only for interrupted runs.
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Do not ask for unbounded traces.
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