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Third-Party Capabilities

Capabilities are the recommended way for third-party packages to extend Pydantic AI, since they can bundle tools with hooks, instructions, and model settings. See Extensibility for the full ecosystem, including third-party toolsets that can also be wrapped as capabilities.

Task Management

Capabilities for task planning and progress tracking help agents organize complex work:

  • pydantic-ai-todo - TodoCapability with add_todo, read_todos, write_todos, update_todo_status, and remove_todo tools. Supports subtasks, dependencies, and PostgreSQL persistence. Also available as a lower-level TodoToolset.

Context Management

Capabilities for managing long conversations help agents stay within context limits:

  • summarization-pydantic-ai - Four capabilities for managing long conversations: ContextManagerCapability (real-time token tracking, auto-compression at a configurable threshold, and large tool-output truncation); SummarizationCapability (LLM-powered history compression); SlidingWindowCapability (zero-cost message trimming); LimitWarnerCapability (injects a finish-soon hint before hard context limits). Also available as standalone history_processors: SummarizationProcessor, SlidingWindowProcessor, and LimitWarnerProcessor.

Multi-Agent Orchestration

Capabilities for spawning and delegating to specialized subagents help agents tackle complex, parallelizable work:

  • subagents-pydantic-ai - SubAgentCapability adds tools for multi-agent delegation: task (spawn a subagent), check_task, wait_tasks, list_active_tasks, soft_cancel_task, hard_cancel_task, and answer_subagent. Supports sync, async, and auto execution modes, nested subagents, and runtime agent creation. Also available as a lower-level toolset via create_subagent_toolset.

Guardrails & Safety

Capabilities for cost control, input/output filtering, and tool permissions help keep agents safe and within budget:

  • pydantic-ai-shields - Ready-to-use guardrail capabilities: CostTracking (tracks token usage and USD cost per run, raises BudgetExceededError on budget overrun); ToolGuard (block or require approval for specific tools); InputGuard and OutputGuard (custom sync or async validation functions); PromptInjection, PiiDetector, SecretRedaction, BlockedKeywords, and NoRefusals content shields.

File Operations & Sandboxing

Capabilities for filesystem access and sandboxed code execution help agents work with files and run code safely:

  • pydantic-ai-backend - ConsoleCapability registers ls, read_file, write_file, edit_file, glob, grep, and execute tools with a fine-grained permission system. Backends include StateBackend (in-memory, for testing), LocalBackend (real filesystem), DockerSandbox (isolated container execution), and CompositeBackend (routing across backends). Also available as a lower-level ConsoleToolset.

Agent Skills

Capabilities that implement Agent Skills support help agents efficiently discover and perform specific tasks:

  • pydantic-ai-skills - SkillsCapability implements Agent Skills support with progressive disclosure (load skills on-demand to reduce tokens). Supports filesystem and programmatic skills; compatible with agentskills.io.

Data & Analytics

Capabilities for querying and analyzing structured data help agents answer questions over files and databases:

  • pydantic-ai-chdb - ChDBCapability gives agents analytical SQL over local files (Parquet/CSV/JSON), object storage, and remote databases with chDB, the in-process ClickHouse engine — the engine itself needs no server or connection string to run (remote sources are reached via ClickHouse table functions, which take their own credentials). Registers run_select_query (read-only ClickHouse SQL with parameter binding), list_databases, list_tables, describe_table, get_sample_data, list_functions, and attach_file (opt-in writable sessions) tools plus schema-first instructions. Sessions default to the engine-level readonly=2 setting with capped results, and typed engine errors are mapped to ModelRetry so the model can correct its queries. Works with agent specs out of the box, so it can be loaded via from_spec / Agent.from_spec. Also available as a lower-level toolset via ChDBCapability(...).get_toolset().

To add your package to this page, open a pull request.

To publish your own capability package, see Publishing capabilities and Extensibility.