pydantic-ai-harness
Extend Pydantic AI agents with batteries-included capabilities from pydantic-ai-harness — currently Code Mode, which collapses many tool calls into one sandboxed Python execution. Use when the user mentions pydantic-ai-harness, CodeMode, Monty, code mode, or tool sandboxing, when they want an agent to run agent-written Python, or when a Pydantic AI agent would benefit from orchestrating multiple tool calls in a single sandboxed script.
What this skill does
# Building with Pydantic AI Harness
Pydantic AI Harness is the official capability library for Pydantic AI. Capabilities that need model or
framework support — and those fundamental to every agent — live in core `pydantic-ai`; optional,
batteries-included capabilities live here. Both are composed onto an agent through the same
`capabilities=[...]` API.
This skill covers the capabilities shipped by `pydantic-ai-harness`. For the core framework — agents,
tools, structured output, hooks, and testing — use the `building-pydantic-ai-agents` skill instead.
## When to Use This Skill
Invoke this skill when:
- The user mentions `pydantic-ai-harness`, `CodeMode`, code mode, or the Monty sandbox
- An agent makes many sequential tool calls that could collapse into one sandboxed Python execution
- The user wants the model to write Python that loops, branches, aggregates, or parallelizes tool calls with `asyncio.gather`
- The user asks to sandbox or constrain the code an agent runs
Do **not** use this skill for:
- Core Pydantic AI usage — building agents, adding tools, structured output, streaming, or testing (use `building-pydantic-ai-agents`)
- Capabilities that ship in core `pydantic-ai`, such as web search, tool search, and thinking
- The Pydantic validation library on its own (`pydantic`/`BaseModel` without agents)
## Supported Capabilities
| Capability | Description | Reference |
|---|---|---|
| `CodeMode` | Wraps eligible tools into a single sandboxed `run_code` tool so the model orchestrates them in Python | [Code Mode](./references/CODE-MODE.md) |
More capability areas are tracked in the
[capability matrix](https://github.com/pydantic/pydantic-ai-harness#capability-matrix); as they stabilize,
this skill grows to cover them.
## Install
```bash
uv add pydantic-ai-harness
```
Each capability declares its own extra. Code Mode needs the Monty sandbox:
```bash
uv add "pydantic-ai-harness[codemode]" # `code-mode` is also accepted as an alias
```
Requires Python 3.10+ and `pydantic-ai-slim>=1.95.1`.
## Quick Start
A harness capability is added to the agent like any other. Here `CodeMode` wraps an MCP server's tools into
a single `run_code` tool that the model drives with Python.
```python {test="skip"}
from pydantic_ai import Agent
from pydantic_ai.capabilities import MCP # MCP ships in core pydantic-ai
from pydantic_ai_harness import CodeMode
agent = Agent(
'anthropic:claude-sonnet-4-6',
capabilities=[
# native=False routes the MCP tools through a local toolset so CodeMode can wrap them.
# Without it, providers with native MCP run the tools server-side and bypass the sandbox.
MCP('https://hn.caseyjhand.com/mcp', native=False),
CodeMode(),
],
)
result = agent.run_sync(
'Across the top and best Hacker News feeds, find the most-discussed story with at '
'least 100 points and summarize its comment thread in one paragraph.'
)
print(result.output)
#> The most-discussed story clearing 100 points is ...
```
Instead of one model round-trip per tool call, the model writes a single Python script that fetches both
feeds with `asyncio.gather`, dedupes and ranks them in plain Python, and pulls the winning thread —
collapsing many calls into one `run_code`.
## Key Practices
- **Confirm a harness capability is actually needed.** If core Pydantic AI tools and capabilities are enough, use the `building-pydantic-ai-agents` skill instead — don't reach for the harness by default.
- **Read the reference before writing code.** Each capability has its own configuration, constraints, and gotchas — load the linked reference (e.g. [Code Mode](./references/CODE-MODE.md)) first.
- **Install the capability's extra.** Importing `CodeMode` without `pydantic-ai-harness[codemode]` raises an `ImportError`; the Monty sandbox is an optional dependency.
## Common Gotchas
- **`native=True` tools bypass `CodeMode`.** Provider-native MCP servers and web search execute server-side, so `run_code` never sees them. Construct them with `native=False` to keep them local and wrappable.
- **The Monty sandbox is a Python subset.** No class definitions, no third-party imports, and only a small stdlib allowlist — read [Code Mode](./references/CODE-MODE.md#sandbox-restrictions) before debugging generated code that fails to run.
- **`CodeMode` needs its extra.** Install `pydantic-ai-harness[codemode]`, not the bare package.
Related in AI Agents
skill-development
IncludedComprehensive meta-skill for creating, managing, validating, auditing, and distributing Claude Code skills and slash commands (unified in v2.1.3+). Provides skill templates, creation workflows, validation patterns, audit checklists, naming conventions, YAML frontmatter guidance, progressive disclosure examples, and best practices lookup. Use when creating new skills, validating existing skills, auditing skill quality, understanding skill architecture, needing skill templates, learning about YAML frontmatter requirements, progressive disclosure patterns, tool restrictions (allowed-tools), skill composition, skill naming conventions, troubleshooting skill activation issues, creating custom slash commands, configuring command frontmatter, using command arguments ($ARGUMENTS, $1, $2), bash execution in commands, file references in commands, command namespacing, plugin commands, MCP slash commands, Skill tool configuration, or deciding between skills vs slash commands. Delegates to docs-management skill for official documentation.
reprompter
IncludedTransform messy prompts into well-structured, effective prompts — single or multi-agent. Use when: "reprompt", "reprompt this", "clean up this prompt", "structure my prompt", rough text needing XML tags and best practices, "reprompter teams", "repromptception", "run with quality", "smart run", "smart agents", multi-agent tasks, audits, parallel work, anything going to agent teams. Don't use when: simple Q&A, pure chat, immediate execution-only tasks. See "Don't Use When" section for details. Outputs: Structured XML/Markdown prompt, quality score (before/after), optional team brief + per-agent sub-prompts, agent team output files. Success criteria: Single mode quality score ≥ 7/10; Repromptception per-agent prompt quality score 8+/10; all required sections present, actionable and specific.
adaptive-compaction
IncludedAdaptive add-on policy and recovery layer that decides WHEN to compact, prune, snapshot, or fork -- replacing fixed-percent auto-compaction across Claude Code, Codex, and MCP-capable hosts. Trigger on auto-compact timing or damage: "when should I compact", "is it safe to compact now or start a fresh session", "auto-compact fires too early/mid-task", "switching to an unrelated task but the window still has space", "context rot", "answers get worse the longer the session runs", "the agent forgot the plan or my decisions after it summarized", "add a layer on top that manages context without changing the agent", raising autoCompactWindow to give the policy room, or installing/tuning a cross-tool compaction policy or PreCompact hook -- even when "compaction" is never said but the problem is context-window pressure or post-summarization memory loss. Do NOT use to summarize a conversation, build RAG, write a summarization prompt (decides WHEN not HOW), or answer max-context-length trivia.
agent-skill-creator
IncludedCreate cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, and spec validation.
llm-wiki
IncludedUse when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates entity/concept pages, maintains cross-references, and keeps a synthesis current. Triggers include "second brain", "Obsidian wiki", "personal knowledge management", "ingest this paper/article/book", "build a research wiki", "compound knowledge", "Memex", or whenever the user wants knowledge to accumulate across sessions instead of being re-derived by RAG on every query.
skill-master
IncludedAgent Skills authoring, evaluation, and optimization. Create, edit, validate, benchmark, and improve skills following the agentskills.io specification. Use when designing SKILL.md files, structuring skill folders (references, scripts, assets), ingesting external documentation into skills, running trigger evals, benchmarking skill quality, optimizing descriptions, or performing blind A/B comparisons. Keywords: agentskills.io, SKILL.md, skill authoring, eval, benchmark, trigger optimization.