docs: add pydantic-deep to third-party toolsets

docs/multi-agent-applications.md

@@ -1,11 +1,12 @@
 # Multi-agent Applications
 
-There are roughly four levels of complexity when building applications with Pydantic AI:
+There are roughly five levels of complexity when building applications with Pydantic AI:
 
 1. Single agent workflows — what most of the `pydantic_ai` documentation covers
 2. [Agent delegation](#agent-delegation) — agents using another agent via tools
 3. [Programmatic agent hand-off](#programmatic-agent-hand-off) — one agent runs, then application code calls another agent
 4. [Graph based control flow](graph.md) — for the most complex cases, a graph-based state machine can be used to control the execution of multiple agents
+5. [Deep Agents](#deep-agents) — production-grade agents with planning, file operations, task delegation, and sandboxed code execution
 
 Of course, you can combine multiple strategies in a single application.
 
@@ -322,8 +323,23 @@ graph TB
 
 See the [graph](graph.md) documentation on when and how to use graphs.
 
+## Deep Agents
+
+Deep agents are production-grade autonomous agents that go beyond simple tool use. They combine multiple architectural patterns to handle complex, multi-step tasks reliably:
+
+- **Planning and progress tracking** — agents break down complex tasks into steps and track their progress, giving users visibility into what the agent is working on
+- **File system operations** — reading, writing, and editing files with proper abstraction layers that work across in-memory storage, real file systems, and sandboxed containers
+- **Task delegation** — spawning specialized sub-agents for specific tasks, with isolated context to prevent recursive delegation issues
+- **Sandboxed code execution** — running AI-generated code in isolated environments (typically Docker containers) to prevent accidents
+- **Context management** — automatic conversation summarization to handle long sessions that would otherwise exceed token limits
+- **Human-in-the-loop** — approval workflows for dangerous operations like code execution or file deletion
+
+These patterns emerged from teams building production agents (like [Claude Code](https://docs.anthropic.com/en/docs/agents-and-tools/claude-code/overview) and [Manus](https://manus.im/)) and discovering what actually works at scale.
+
+[Pydantic-Deep](https://github.com/vstorm-co/pydantic-deepagents) implements these deep agent patterns for Pydantic AI. See the [toolsets documentation](toolsets.md#pydantic-deep) for usage examples and the [full demo application](https://github.com/vstorm-co/pydantic-deepagents/tree/main/examples/full_app) for a complete example with a chat interface, file uploads, skills, and streaming responses.
+
 ## Examples
 
-The following examples demonstrate how to use dependencies in Pydantic AI:
+The following examples demonstrate how to use multi-agent patterns in Pydantic AI:
 
 - [Flight booking](examples/flight-booking.md)

docs/toolsets.md

@@ -708,3 +708,18 @@ toolset = ACIToolset(
 
 agent = Agent('openai:gpt-5', toolsets=[toolset])
 ```
+
+### Pydantic-Deep {#pydantic-deep}
+
+[Pydantic-Deep](https://github.com/vstorm-co/pydantic-deepagents), built by [Vstorm](https://vstorm.co/), brings deep agent patterns to Pydantic AI. Deep agents are production-grade agents with planning, file system operations, task delegation, and sandboxed code execution — patterns derived from production systems like Claude Code and Manus.
+
+Available toolsets:
+
+- `TodoToolset`: Task planning and progress tracking for agent self-organization
+- `FilesystemToolset`: File operations (ls, read, write, edit, glob, grep, execute)
+- `SubAgentToolset`: Spawn and delegate tasks to specialized subagents
+- `SkillsToolset`: Load and use [agent skills](https://www.anthropic.com/engineering/equipping-agents-for-the-real-world-with-agent-skills) from markdown files
+
+The framework also includes multiple backends (in-memory, filesystem, Docker sandbox), automatic conversation summarization, and human-in-the-loop approval workflows.
+
+See the [documentation](https://vstorm-co.github.io/pydantic-deepagents/) for installation and usage, or explore the [full demo application](https://github.com/vstorm-co/pydantic-deepagents/tree/main/examples/full_app) for a complete example with a chat interface, file uploads, skills, and streaming responses.