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 commands/alphaaiservice/cortex/gen-testsgit clone --depth 1 https://github.com/alphaaiservice/cortexWhat 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 | $0.00029 | $0.00641 |
| Opus 5 | $0.00015 | $0.00320 |
| Sonnet 5 | $0.00006 | $0.00128 |
| Haiku 4.5 | $0.00003 | $0.00064 |
Grade A, and why
gen-tests 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Automated Test Generation
Generate comprehensive tests for: $ARGUMENTS
Step 1: Analyze Target
- Read the target file(s) specified in $ARGUMENTS
- If
--all-untested, find all source files without corresponding test files - Identify the testing framework already in use (Jest, Vitest, Pytest, JUnit, Go testing)
- Understand existing test patterns in the project
Step 2: Analyze Functions/Methods
For each function/method/class in the target:
- Identify input parameters and their types
- Map all code paths (branches, loops, early returns)
- Identify external dependencies to mock
- Determine expected outputs for each path
- Find edge cases (null, empty, boundary values, overflow)
Step 3: Generate Test File
Create test file following project conventions:
Test Structure
describe('[ModuleName]', () => {
describe('[functionName]', () => {
// Happy path tests
it('should [expected behavior] when [condition]', () => {})
// Edge cases
it('should handle empty input', () => {})
it('should handle null/undefined', () => {})
// Error cases
it('should throw [ErrorType] when [condition]', () => {})
// Boundary tests
it('should handle maximum/minimum values', () => {})
})
})
Test Categories to Generate
- Happy path — Normal expected usage (at least 2 tests per function)
- Edge cases — Empty, null, undefined, zero, max values
- Error handling — Invalid inputs, network failures, timeouts
- Integration — How the module interacts with dependencies
- Regression — Tests for any known bugs or tricky logic
Step 4: Mock Strategy
- Use existing mock patterns from the project
- Mock external APIs, databases, and file system
- Create fixture files if needed
- Use factory patterns for test data
Step 5: Verify Tests
# Run the generated tests
npm test -- --testPathPattern=[test-file] 2>&1 || pytest [test-file] -v 2>&1
Fix any failing tests. Ensure all tests pass before finishing.
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 · 90 lines · 29 tokens per session scan A 52f6c8d3ccb6
gen-tests is a command published in the GitHub repository alphaaiservice/cortex (1 stars, last pushed 26d ago), licensed MIT. It adds 29 tokens to every session and 641 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 2026-08-31.
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