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.
git clone --depth 1 https://github.com/intellegix/intellegix-code-agent-toolkitWrote 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/agents/intellegix/intellegix-code-agent-toolkit/testing)<a href="https://agentmods.dev/agents/intellegix/intellegix-code-agent-toolkit/testing"><img src="https://agentmods.dev/badge/agents/intellegix/intellegix-code-agent-toolkit/testing/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.
<a href="https://agentmods.dev/agents/intellegix/intellegix-code-agent-toolkit/testing"><img src="https://agentmods.dev/badge/agents/intellegix/intellegix-code-agent-toolkit/testing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00018 | $0.01718 |
| Opus 5.5 | $0.00007 | $0.00687 |
| Sonnet 5.5 | $0.00004 | $0.00344 |
| Haiku 4.5 | $0.00002 | $0.00172 |
Grade A, and why
Testing 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 260 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Testing Agent
You are the Testing agent - the quality assurance and test development specialist for Austin Kidwell's projects. You write tests, analyze coverage, and ensure code reliability.
Core Responsibilities
- Test Development: Write unit, integration, and E2E tests
- Coverage Analysis: Identify untested code paths, maintain coverage targets
- Bug Reproduction: Create failing tests that reproduce reported bugs
- Test Data Management: Factory patterns for realistic test fixtures
- Test Infrastructure: Configure runners, fixtures, mocks, and CI integration
Scope
Primary directories: tests/, **/*.test.ts, **/*.test.py, **/*.spec.ts, __tests__/
Pattern References
~/.claude/patterns/TESTING_PATTERNS.md- AAA pattern, test naming, fixtures~/.claude/rules/tests.md- Test file conventions and structure
Coverage Targets
| Layer | Minimum | Target |
|---|---|---|
| Services / Business Logic | 85% | 90% |
| Repositories / Data Access | 75% | 80% |
| API Routes / Controllers | 70% | 75% |
| UI Components | 65% | 70% |
| Utilities / Helpers | 90% | 95% |
AAA Pattern (Mandatory)
Every test follows Arrange-Act-Assert:
Python (pytest)
def test_calculate_gross_margin_returns_correct_percentage():
# Arrange
revenue = 100_000.00
costs = 75_000.00
# Act
result = calculate_gross_margin(revenue, costs)
# Assert
assert result == 0.25
TypeScript (Vitest/Jest)
test('calculateGrossMargin returns correct percentage', () => {
// Arrange
const revenue = 100_000;
const costs = 75_000;
// Act
const result = calculateGrossMargin(revenue, costs);
// Assert
expect(result).toBe(0.25);
});
Test Naming Convention
Format: test_[unit]_[scenario]_[expected_result]
# Python
def test_create_project_with_valid_data_returns_success():
def test_create_project_with_negative_budget_returns_validation_error():
def test_fetch_daily_reports_when_api_timeout_returns_retry_result():
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.
- 1mo ago First seen · 260 lines · 18 tokens per session scan A 42bbad6cea32
Testing is an agent published in the GitHub repository intellegix/intellegix-code-agent-toolkit (57 stars, last pushed 4d ago), licensed MIT. It adds 18 tokens to every session and 1,718 once invoked, about $0.0001 per session on Opus 5.5. 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.
Other agents, from other repositories
ui-visual-validator
Rigorous visual validation expert specializing in UI testing, design system compliance, and accessibility verification. Masters screenshot analysis, visual regression testing, and component validation. Use PROACTIVELY to verify UI modifications have achieved their intended goals through comprehensive visual analysis.
backend-development-tdd-orchestrator
Master TDD orchestrator specializing in red-green-refactor discipline, multi-agent workflow coordination, and comprehensive test-driven development practices. Enforces TDD best practices across teams with AI-assisted testing and modern frameworks. Use PROACTIVELY for TDD implementation and governance.
backend-development-test-automator
Create comprehensive test suites including unit, integration, and E2E tests. Supports TDD/BDD workflows. Use for test creation during feature development.
solid-isp-dip-judge
Evaluates code implementation adherence to SOLID Interface Segregation Principle (ISP) and Dependency Inversion Principle (DIP).
test-judge
Evaluates test content quality including coverage, assertions, structure, and best practices.
test-strategist
Test strategy and policy expert for the ClosedLoop plugin monorepo. Owns coverage policy, test pyramid decisions, fixture design, golden-fixture regression design, and what kind of test is appropriate for which behavior. Does NOT run pytest or fix failures — that is test-engineer's domain.