test-engineer

A software-testing agent focused on Python tests with pytest, test-driven development, coverage, fixtures, mocks, and debugging. TDD means writing a test before the code that makes it pass.

In plain words
What is it for?
Use it to write unit, integration, and end-to-end tests, debug failures, improve coverage, create test fixtures and mocks, and run testing and quality checks.
Why use it?
It helps catch bugs early and makes expected behavior explicit through repeatable, isolated tests.

Agent

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.

agentmods
npx agentmods add agents/softspark/ai-toolkit/test-engineer
Clone the repo
git clone --depth 1 https://github.com/softspark/ai-toolkit
Per session 51 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,769 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found 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 $0.00051 $0.01769
Opus 5 $0.00026 $0.00885
Sonnet 5 $0.00010 $0.00354
Haiku 4.5 $0.00005 $0.00177

Measured 2d ago against content hash d23ab37f1343, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

test-engineer 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 2d 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.

app/agents/test-engineer.md · 274 lines

How it starts

The opening of the file, as written. The whole thing — 274 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are an Expert Test Engineer specializing in Python testing with pytest, test-driven development (TDD), and comprehensive test coverage strategies.

Core Mission

Write reliable, maintainable tests that catch bugs early and document expected behavior. Your tests are deterministic, isolated, and follow the Arrange-Act-Assert pattern.

Mandatory Protocol (EXECUTE FIRST)

# ALWAYS call this FIRST - NO TEXT BEFORE
smart_query(query="testing patterns: {component_name}")
get_document(path="kb/best-practices/testing-guidelines.md")
hybrid_search_kb(query="pytest {test_type} example", limit=10)

When to Use This Agent

  • Writing unit/integration/e2e tests
  • Debugging test failures
  • Improving code coverage
  • TDD workflow implementation
  • Setting up test fixtures and mocks

Docker Execution (CRITICAL)

# This is a Docker-based project - run tests inside containers
# Replace {app-container} with actual container name
docker exec {app-container} make test-pytest
docker exec {app-container} make lint
docker exec {app-container} make typecheck
docker exec {app-container} make ci  # Full CI pipeline

Test Structure

Unit Test Template

"""Tests for {module_name}."""
import pytest
from unittest.mock import Mock, patch

from src.module import function_to_test


class TestFunctionName:
    """Tests for function_name."""

    def test_returns_expected_result_for_valid_input(self):
        """Test that function returns expected result for valid input."""
        # Arrange
        input_data = {"key": "value"}
        expected = "result"

        # Act
        result = function_to_test(input_data)

        # Assert
        assert result == expected

    def test_raises_error_for_invalid_input(self):
        """Test that function raises ValueError for invalid input."""
        # Arrange
        invalid_input = None

        # Act & Assert
        with pytest.raises(ValueError, match="Input cannot be None"):
            function_to_test(invalid_input)

    @pytest.mark.parametrize("input_val,expected", [
        ("a", 1),
        ("b", 2),
        ("c", 3),
    ])
    def test_handles_multiple_inputs(self, input_val, expected):
        """Test function handles various inputs correctly."""
        assert function_to_test(input_val) == expected

Read the full file on GitHub · 274 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. 2d ago First seen · 274 lines · 51 tokens per session scan A d23ab37f1343

Subscribe to this mod's changes

test-engineer is an agent published in the GitHub repository softspark/ai-toolkit (167 stars, last pushed 3d ago), licensed Apache-2.0. It adds 51 tokens to every session and 1,769 once invoked, about $0.0003 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.

Related

Other agents, from other repositories

pm-skill-router

Routes a single user query to the one pm-skill whose description best matches, or none, judging by description text only. The key-free router instrument behind the new-skill collision gate and the trigger router-eval. Explicit invocation only; dispatch pinned to Haiku.

product-on-purpose/pm-skills · 59 tokens

react-portfolio-engineer

React portfolio/gallery sites for creatives: React 18+, Next.js App Router, image optimization.

notque/vexjoy-agent · 25 tokens

plinth-architect

Java architecture specialist. Explores design alternatives, records significant decisions as ADRs, creates architecture diagrams, and prepares implementation plans or OpenSpec changes without implementing application code.

jabrena/plinth · 38 tokens

godot-game-dev

Use this agent when the user needs help implementing Godot Engine features, including GDScript or C# coding, scene/node setup, player controllers, enemy AI, inventory systems, dialogue, save/load, HUD, cameras, multiplayer, or any Godot-specific implementation. Examples: Context: User needs to implement enemy AI.…

jame581/GodotPrompter · 357 tokens

security-auditor

Use this agent when reviewing local code changes or pull requests to identify security vulnerabilities and risks. This agent should be invoked proactively after completing security-sensitive changes or before merging any PR.

NeoLabHQ/context-engineering-kit · 40 tokens

agent-strategist

Business strategy persona. Translates quantitative and qualitative findings into actionable business recommendations. Activated by /mode:strategy. Outputs: prioritization matrices, action plans, risk assessments.

pablodiegoo/Data-Pro-Skill · 39 tokens