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An AI-driven testing agent that auto-discovers, generates, executes, evaluates, and fixes tests for any project type. Inspired by the edubites autonomous test runner pattern, generalized for Claude Bootstrap + Maggy.
Passed 19 of 23 test cases with the skill, and 11 of 23 without it.
and 8 more in the full report
10 fixed10 passed either way3 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 10 test cases the skill fixed. Same model, same prompt, with and without the skill.
What CLI command starts continuous test monitoring to automatically discover, run, and fix tests on file changes?
| Checked | Without skill | With skill |
|---|---|---|
| Specifies maggy test watch for continuous test monitoring. | Missed | Passed |
The instructions your model reads when the skill loads.
An AI-driven testing agent that auto-discovers, generates, executes, evaluates, and fixes tests for any project type. Inspired by the edubites autonomous test runner pattern, generalized for Claude Bootstrap + Maggy.
Source Scan → Discover Gaps → Generate Tests → Execute → Evaluate → Report → Fix Loop
Auto-detect project type:
Python → scan for *.py files, extract public functions/classes
TypeScript → scan for *.ts/*.tsx files, extract exports
API → scan FastAPI/Express routes, extract endpoints + methods
Web → scan React/Vue components, extract user flows
Map existing tests:
Python → pytest --collect-only
TypeScript → vitest --list
API → scan tests/ for endpoint coverage
Compute coverage gaps:
- Functions with 0 tests
- API endpoints with 0 tests
- Components with 0 tests
- Branches with <80% coverage
For each uncovered function/endpoint/component:
1. Read source code → understand inputs, outputs, edge cases
2. Generate test scaffold using ~/bin/deepseek --pro
3. Include: happy path, error cases, edge cases, auth checks
test cases passed, vs 11 / 23 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.