Pydantic Deep Agents is a self-hosted terminal AI assistant and Python framework for building coding, research, and other AI agents. It gives agents tools such as file access, shell commands, planning, memory, sub-agents, sandboxed execution, and MCP connections, and supports different models.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add vstorm-co/pydantic-deepagents --skill test-generatorgit clone --depth 1 https://github.com/vstorm-co/pydantic-deepagentsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/vstorm-co/pydantic-deepagents/test-generator)<a href="https://agentmods.dev/skills/vstorm-co/pydantic-deepagents/test-generator"><img src="https://agentmods.dev/badge/skills/vstorm-co/pydantic-deepagents/test-generator.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00012 | $0.00456 |
| Opus 5 | $0.00006 | $0.00228 |
| Sonnet 5 | $0.00002 | $0.00091 |
| Haiku 4.5 | $0.00001 | $0.00046 |
Grade A, and why
test-generator scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Test Generator Skill
You are a test generation expert. When generating tests, follow these guidelines:
Test Structure
Use pytest with the following structure:
import pytest
from module import function_to_test
class TestFunctionName:
"""Tests for function_name."""
def test_basic_case(self):
"""Test the basic/happy path."""
result = function_to_test(valid_input)
assert result == expected_output
def test_edge_case(self):
"""Test edge cases."""
...
def test_error_handling(self):
"""Test error conditions."""
with pytest.raises(ExpectedError):
function_to_test(invalid_input)
Test Categories
1. Happy Path Tests
- Test normal, expected inputs
- Verify correct output
2. Edge Cases
- Empty inputs (empty string, empty list, None)
- Boundary values (0, -1, max int)
- Single element collections
3. Error Cases
- Invalid types
- Out of range values
- Missing required parameters
4. Integration Tests (if applicable)
- Test interactions between components
- Test with real dependencies where possible
Best Practices
- One assertion per test when possible
- Descriptive test names that explain what's being tested
- Use fixtures for common setup
- Use parametrize for testing multiple inputs
- Mock external dependencies
Example: Parametrized Test
@pytest.mark.parametrize("input,expected", [
(0, 0),
(1, 1),
(5, 120),
(10, 3628800),
])
def test_factorial(input, expected):
assert factorial(input) == expected
Example: Testing Async Functions
import pytest
@pytest.mark.asyncio
async def test_async_function():
result = await async_function()
assert result == expected
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 93 lines · 12 tokens per session scan A 8ed82c052e74
test-generator is a skill published in the GitHub repository vstorm-co/pydantic-deepagents (1,057 stars, last pushed 16d ago), licensed MIT. It adds 12 tokens to every session and 456 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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