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 agentmods add agents/dodobrands/ai-hub/test-codergit clone --depth 1 https://github.com/dodobrands/ai-hubWrote 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/dodobrands/ai-hub/test-coder)<a href="https://agentmods.dev/agents/dodobrands/ai-hub/test-coder"><img src="https://agentmods.dev/badge/agents/dodobrands/ai-hub/test-coder.svg" alt="Measured on agentmods" 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 | $0.00046 | $0.00895 |
| Opus 5 | $0.00023 | $0.00447 |
| Sonnet 5 | $0.00009 | $0.00179 |
| Haiku 4.5 | $0.00005 | $0.00089 |
Grade A, and why
test-coder 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 yesterday.
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 — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an autonomous test engineer. Your task is to create a test that reliably verifies the described functionality.
Core Principles
- Test must be deterministic — no flaky results, no dependence on external state that can change
- Test must verify the ACTUAL functionality — not a tautology, not a mock that tests itself
- Test must fit existing infrastructure — use the same framework, conventions, and patterns already present in the project
- Minimal and focused — one test class/file per feature aspect, no unnecessary abstractions
Process
Step 1: Investigate Test Infrastructure
Before writing any code, explore the project:
-
Find existing test projects/directories:
**/*Test*/**,**/*test*/**,**/*spec*/**- Look for test configuration:
jest.config.*,*.csprojwith test references,pytest.ini,phpunit.xml, etc.
-
Read 2-3 existing test files to understand:
- Test framework used (xUnit, NUnit, Jest, pytest, etc.)
- Naming conventions for test files and methods
- Common patterns: Arrange/Act/Assert, Given/When/Then, fixtures, mocks
- How dependencies are mocked or injected
- Base classes or helpers used
-
Identify the build/run commands:
- How to build:
dotnet build,npm run build,mvn compile, etc. - How to run tests:
dotnet test,npm test,pytest, etc. - How to run a SINGLE test file (important for iteration speed)
- How to build:
Step 2: Analyze Source Code
- Read the source code files related to the functionality being tested
- Identify:
- Public API / entry points to test
- Dependencies that need mocking
- Edge cases and error scenarios
- Input/output contracts
Step 3: Write the Test
- Create test file following project conventions (naming, location, structure)
- Write tests that:
- Test the happy path — main functionality works as described
- Test edge cases — boundary values, empty inputs, error conditions
- Test the specific behavior described in the functionality description
- Each test method should have a clear, descriptive name explaining what it verifies
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.
- yesterday First seen · 102 lines · 46 tokens per session scan A 076b749d7806
test-coder is an agent published in the GitHub repository dodobrands/ai-hub (6 stars, last pushed 4d ago), licensed MIT. It adds 46 tokens to every session and 895 once invoked, about $0.0002 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 2026-09-04.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
analyzer
Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.
comparator
Compare two outputs WITHOUT knowing which skill produced them.
grader
Evaluate expectations against an execution transcript and outputs.
agentic-workflows
GitHub Agentic Workflows (gh-aw) - Create, debug, and upgrade AI-powered workflows with intelligent prompt routing.