testing-python

testing-python is a skill for Claude Code, Codex from benchflow-ai/skillsbench. It costs 45 tokens per session (1,211 once invoked), scanned A, a copy of python-tests, Apache-2.0.

A guide to writing Python tests with pytest, a tool for checking that Python code behaves as expected. It covers isolated tests, reusable test setup, varied inputs, mocks, and asynchronous code.

In plain words
What is it for?
Use it to write, review, debug, and organize Python unit tests.
Why use it?
It helps make test failures easier to understand and improves coverage of individual behaviors without mixing unrelated checks together.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to write, review, debug, and organize Python unit tests.

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Install with agentmods
npx agentmods add skills/benchflow-ai/skillsbench/testing-python
About the project

SkillsBench is a benchmark for measuring how effectively AI agents use modular skills—folders containing instructions, scripts, and resources—to complete specialized tasks. It helps researchers and developers evaluate both skill quality and agent behavior, including tasks that require combining multiple skills. The catalogue’s skills and instructions are evaluated as part of this workflow.

benchflow-ai/skillsbench · 1,764 stars · on GitHub · skillsbench.ai

Install

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.

Any agent
npx skills add benchflow-ai/skillsbench --skill testing-python
Clone the repo
git clone --depth 1 https://github.com/benchflow-ai/skillsbench

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for testing-python

README.md
[![agentmods](https://agentmods.dev/badge/skills/benchflow-ai/skillsbench/testing-python/github.svg)](https://agentmods.dev/skills/benchflow-ai/skillsbench/testing-python)
Your own site
<a href="https://agentmods.dev/skills/benchflow-ai/skillsbench/testing-python"><img src="https://agentmods.dev/badge/skills/benchflow-ai/skillsbench/testing-python/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for testing-python

Your own site · 80×15
<a href="https://agentmods.dev/skills/benchflow-ai/skillsbench/testing-python"><img src="https://agentmods.dev/badge/skills/benchflow-ai/skillsbench/testing-python.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 45 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,211 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00045 $0.01211
Opus 5 $0.00023 $0.00606
Sonnet 5 $0.00009 $0.00242
Haiku 4.5 $0.00005 $0.00121

Measured 9d ago against content hash 2741f4b02a70, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

testing-python 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 9d 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.

Origin

This is a copy

100% identical to python-tests — 226 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

tasks/fix-build-agentops/environment/skills/testing-python/SKILL.md · 221 lines

How it starts

The opening of the file, as written. The whole thing — 221 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Writing Effective Python Tests

Core Principles

Every test should be atomic, self-contained, and test single functionality. A test that tests multiple things is harder to debug and maintain.

Test Structure

Atomic unit tests

Each test should verify a single behavior. The test name should tell you what's broken when it fails. Multiple assertions are fine when they all verify the same behavior.

# Good: Name tells you what's broken
def test_user_creation_sets_defaults():
    user = User(name="Alice")
    assert user.role == "member"
    assert user.id is not None
    assert user.created_at is not None

# Bad: If this fails, what behavior is broken?
def test_user():
    user = User(name="Alice")
    assert user.role == "member"
    user.promote()
    assert user.role == "admin"
    assert user.can_delete_others()

Use parameterization for variations of the same concept

import pytest

@pytest.mark.parametrize("input,expected", [
    ("hello", "HELLO"),
    ("World", "WORLD"),
    ("", ""),
    ("123", "123"),
])
def test_uppercase_conversion(input, expected):
    assert input.upper() == expected

Use separate tests for different functionality

Don't parameterize unrelated behaviors. If the test logic differs, write separate tests.

Project-Specific Rules

No async markers needed

This project uses asyncio_mode = "auto" globally. Write async tests without decorators:

# Correct
async def test_async_operation():
    result = await some_async_function()
    assert result == expected

# Wrong - don't add this
@pytest.mark.asyncio
async def test_async_operation():
    ...

Imports at module level

Put ALL imports at the top of the file:

# Correct
import pytest
from fastmcp import FastMCP
from fastmcp.client import Client

async def test_something():
    mcp = FastMCP("test")
    ...

# Wrong - no local imports
async def test_something():
    from fastmcp import FastMCP  # Don't do this
    ...

Read the full file on GitHub · 221 lines

Changes

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.

  1. 9d ago First seen · 221 lines · 45 tokens per session scan A 2741f4b02a70

Subscribe to this mod's changes

testing-python is a skill published in the GitHub repository benchflow-ai/skillsbench (1,764 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 45 tokens to every session and 1,211 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to python-tests, differing in 226 lines, and is treated as a copy.