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docs: align workbench example with README #637

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4 changes: 2 additions & 2 deletions first-agent.mdx
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Original file line number Diff line number Diff line change
Expand Up @@ -33,7 +33,7 @@ agent_os = AgentOS(agents=[workbench], tracing=True, db=SqliteDb(db_file="agno.d
app = agent_os.get_app()
```

`Workspace(".")` scopes the agent to the current directory. `read`, `list`, and `search` run freely; `write`, `edit`, `move`, `delete`, and `shell` require human approval.
`Workspace(".")` scopes the agent to the current directory. `read`, `list`, and `search` run freely; `write`, `edit`, `delete`, and `shell` require human approval.

## 2. Run Your AgentOS

Expand Down Expand Up @@ -122,7 +122,7 @@ Use it to test, monitor, and manage your agents in real time.

The agent reads your workspace and answers grounded in what it actually finds.

Try a follow-up like "summarize the README" or "create a NOTES.md with three bullet takeaways". The second one will pause for your approval before the file is written, since `write_file` is a confirm-required tool by default.
Try a follow-up like "summarize the README" or "create a NOTES.md with three bullet takeaways". The second one will pause for your approval before the file is written, since `write` is in the confirm list.

Click Sessions or Traces in the sidebar to inspect stored conversations.

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13 changes: 8 additions & 5 deletions index.mdx
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Expand Up @@ -21,24 +21,27 @@
<CodeGroup>

```python Agno SDK
from agno.os import AgentOS
from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.os import AgentOS
from agno.tools.workspace import Workspace

agent = Agent(
name="Agno Agent",
workbench = Agent(
name="Workbench",
model="openai:gpt-5.4",
tools=[Workspace(".",
allowed=["read", "list", "search"],
confirm=["write", "edit", "delete", "shell"],
)],
enable_agentic_memory=True,
add_history_to_context=True,
num_history_runs=3,
)

agent_os = AgentOS(
agents=[agent],
agents=[workbench],
tracing=True,
db=SqliteDb(db_file="tmp/agentos.db"),
db=SqliteDb(db_file="agno.db"),
)
app = agent_os.get_app()
```
Expand Down Expand Up @@ -116,11 +119,11 @@

20 lines of code and you have a FastAPI backend with 50+ endpoints, persisted sessions, tracing, scheduling and RBAC. Interact using the AgentOS UI, Slack, Discord or build a product on top.

Run native Agno agents next to Claude Code, LangGraph and DSPy agents in the same AgentOS.

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index.mdx#L122 

Did you really mean 'DSPy'?

## Agno features

- [**Production API.**](/runtime/serve-as-api) 50+ endpoints with SSE and websockets make it easy to build a product on top of your agent platform.

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Did you really mean 'websockets'?
- [**Storage.**](/runtime/storage) Store sessions, memory, knowledge, and traces in your own database. Use postgres for quick read/write data like sessions and memory. Use clickhouse for OLAP data like traces.
- [**100+ integrations.**](/tools/toolkits/overview) Integrate with 100+ tools using pre-built toolkits.
- [**Context Providers.**](/runtime/context) Use strategies like context providers to access live data stored in Slack, Drive, wikis, MCP, and custom sources.
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