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* Change model from gpt-4.1 to auto in getting-started examples
gpt-4.1 is deprecated. Update all code examples to use 'auto'
for automatic model selection.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* docs: fix formatting that breaks docs.github.com publishing
The docs/ content is synced to docs.github.com (via github/docs-internal),
where it must meet that platform's style rules. Two recurring issues were
being reintroduced and fixed by hand on every sync:
* Unordered lists must use asterisks (*) not hyphens (-) on docs.github.com.
Converted prose bullets in features/fleet-mode.md, features/hooks.md, and
hooks/post-tool-use.md (code blocks and frontmatter left untouched).
* Every table cell must have a value. Filled the empty AZURE_TOKEN_CREDENTIALS
Example cell in setup/azure-managed-identity.md with ManagedIdentityCredential
(matches the row's description and this page's Azure scenario).
Note: intentionally-blank cells that represent structure (optional 'Required'
columns in property tables, section-grouping rows in troubleshooting/
compatibility.md, and the corner cell of the setup/scaling.md comparison
matrix) were left as-is.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Co-authored-by: Scott Addie <10702007+scottaddie@users.noreply.github.com>
Copy file name to clipboardExpand all lines: docs/features/fleet-mode.md
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Good fits include:
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- Multi-file refactors where each worker owns a file, package, or language SDK.
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- Batch reviews where each worker checks a separate diff, module, or alert group.
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- Parallel research across independent repositories, services, or feature areas.
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- Documentation refreshes where each worker owns a page or topic.
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- Migration tasks where each worker can validate its own slice and report back.
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* Multi-file refactors where each worker owns a file, package, or language SDK.
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* Batch reviews where each worker checks a separate diff, module, or alert group.
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* Parallel research across independent repositories, services, or feature areas.
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* Documentation refreshes where each worker owns a page or topic.
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* Migration tasks where each worker can validate its own slice and report back.
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Avoid fleet mode for:
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- Sequential tasks where step 2 needs the concrete output from step 1.
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- Tightly coupled edits where workers would contend for the same files.
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- Small tasks that one synchronous sub-agent or the parent agent can finish quickly.
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- Tasks that require continuous shared reasoning rather than clear ownership.
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* Sequential tasks where step 2 needs the concrete output from step 1.
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* Tightly coupled edits where workers would contend for the same files.
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* Small tasks that one synchronous sub-agent or the parent agent can finish quickly.
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* Tasks that require continuous shared reasoning rather than clear ownership.
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Fleet mode works best when the parent session can create clear units of work, assign one owner per unit, and define what each worker must return.
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## Best practices
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- Decompose the work into independent units before starting fleet mode.
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- Minimize dependencies between todos; dependencies reduce parallelism.
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- Give each todo a durable ID, a clear title, and a complete description.
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- Make each sub-agent own exactly one todo at a time.
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- Use background sub-agents for truly parallel work.
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- Use synchronous sub-agent calls for serialized steps or validation gates.
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- Provide each sub-agent with complete context; sub-agents are stateless across calls.
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- Include file paths, commands, expected outputs, and constraints in each worker prompt.
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- Do not dispatch a single background sub-agent; prefer a synchronous call or batch multiple workers in parallel.
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- Avoid assigning overlapping files to different workers unless the parent agent will reconcile conflicts explicitly.
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- Require every worker to report what it changed, how it validated the change, and what remains blocked.
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- Have the parent agent verify the combined result after workers finish.
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* Decompose the work into independent units before starting fleet mode.
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* Minimize dependencies between todos; dependencies reduce parallelism.
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* Give each todo a durable ID, a clear title, and a complete description.
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* Make each sub-agent own exactly one todo at a time.
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* Use background sub-agents for truly parallel work.
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* Use synchronous sub-agent calls for serialized steps or validation gates.
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* Provide each sub-agent with complete context; sub-agents are stateless across calls.
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* Include file paths, commands, expected outputs, and constraints in each worker prompt.
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* Do not dispatch a single background sub-agent; prefer a synchronous call or batch multiple workers in parallel.
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* Avoid assigning overlapping files to different workers unless the parent agent will reconcile conflicts explicitly.
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* Require every worker to report what it changed, how it validated the change, and what remains blocked.
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* Have the parent agent verify the combined result after workers finish.
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## Limitations and open questions
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- Fleet mode is exposed through generated session RPC bindings and is marked experimental in several SDKs.
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- The SQL todos pattern is the canonical coordination model in the runtime guidance, but whether it is a stable extensibility contract for SDK consumers is still an open question.
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-`subagentStart` and `subagentStop` are runtime hook names; this branch exposes sub-agent lifecycle to SDK consumers through the generic session event stream, not dedicated hook callbacks.
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- Plugin sub-agent registration is configured at the runtime layer through `--plugin-dir`; no SDK-level plugin registration helper was verified on this branch.
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- Java native typed bindings for `session.fleet.start` were not found in the Java SDK source on this branch.
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- Fleet mode does not remove the need for parent-agent review. Parallel workers can produce inconsistent assumptions that the orchestrator must reconcile.
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* Fleet mode is exposed through generated session RPC bindings and is marked experimental in several SDKs.
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* The SQL todos pattern is the canonical coordination model in the runtime guidance, but whether it is a stable extensibility contract for SDK consumers is still an open question.
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*`subagentStart` and `subagentStop` are runtime hook names; this branch exposes sub-agent lifecycle to SDK consumers through the generic session event stream, not dedicated hook callbacks.
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* Plugin sub-agent registration is configured at the runtime layer through `--plugin-dir`; no SDK-level plugin registration helper was verified on this branch.
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* Java native typed bindings for `session.fleet.start` were not found in the Java SDK source on this branch.
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* Fleet mode does not remove the need for parent-agent review. Parallel workers can produce inconsistent assumptions that the orchestrator must reconcile.
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## See also
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-[Custom agents and sub-agent orchestration](custom-agents.md)
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-[Hooks](hooks.md)
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*[Custom agents and sub-agent orchestration](custom-agents.md)
Copy file name to clipboardExpand all lines: docs/hooks/post-tool-use.md
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The `onPostToolUse` hook is called **after** a tool executes **successfully**. Use it to:
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- Transform or filter tool results
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- Log tool execution for auditing
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- Add context based on results
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- Suppress results from the conversation
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* Transform or filter tool results
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* Log tool execution for auditing
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* Add context based on results
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* Suppress results from the conversation
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> **Failure variant** — `onPostToolUse` only fires for successful tool executions. To observe **failed** tool calls, register `onPostToolUseFailure` (`on_post_tool_use_failure` in Python, `OnPostToolUseFailure` in Go/.NET, `on_post_tool_use_failure` in Rust). The handler receives `{ sessionId, toolName, toolArgs, error, timestamp, workingDirectory }` — the `error` field is a string extracted from the tool's failure result — and may return `{ additionalContext: string }` to inject extra guidance for the model (e.g. retry hints). See the [hooks overview](./hooks-overview.md) for the full list.
Copy file name to clipboardExpand all lines: docs/setup/azure-managed-identity.md
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| Variable | Description | Example |
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|----------|-------------|---------|
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|`AZURE_TOKEN_CREDENTIALS`| When running in **Azure**, set it to `ManagedIdentityCredential`. When running **locally**, set it to either `dev` or a developer tool credential name, such as `AzureCliCredential`. ||
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|`AZURE_TOKEN_CREDENTIALS`| When running in **Azure**, set it to `ManagedIdentityCredential`. When running **locally**, set it to either `dev` or a developer tool credential name, such as `AzureCliCredential`. |`ManagedIdentityCredential`|
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|`FOUNDRY_RESOURCE_URL`| Your Microsoft Foundry resource URL |`https://<my-resource>.openai.azure.com`|
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No API key environment variable is needed—authentication is handled by `DefaultAzureCredential`, which automatically supports:
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