testing-assistant
Manages testing lifecycle including unit tests, integration tests, validation, and quality assurance.
Works with
---
name: testing-assistant
description: Manages testing lifecycle including unit tests, integration tests, validation, and quality assurance.
license: MIT
---
# Testing Assistant Skill
Expert system for testing and validating the Claude Patent Creator.
**FOR CLAUDE:** Test scripts in scripts/ directory.
- Go directly to running appropriate test
- Run from project root
- Tests require active venv
- Only run diagnostics if tests fail
## When to Use
Running test suites, validating new features, testing after changes, debugging failures, creating tests, setting up CI/CD, performance testing, E2E validation, regression testing.
## Testing Pyramid
```
/\
/ \ E2E (Manual + Automated)
/----\
/ API \ Integration Tests
/--------\
/ Unit \ Unit Tests
/----------\
```
**Strategy:** More unit tests (fast, isolated), fewer integration (moderate), minimal E2E (slow).
## Test Suite Overview
```bash
scripts/
+-- test_install.py # Complete installation validation
+-- test_gpu.py # GPU detection and CUDA
+-- test_bigquery.py # BigQuery connection
+-- test_analyzers.py # Claims, spec, formalities
+-- test_embedding_speed.py # Performance benchmarks
+-- test_checkpoint.py # Index checkpoint system
```
**Quick Test:**
```bash
python scripts/test_install.py
```
## Manual Testing via Claude
Test MCP tools through Claude Code interface.
### Quick Test Examples
```
1. MPEP Search: "Search MPEP for claim definiteness requirements"
2. Patent Search: "Search for patents about neural networks filed in 2024"
3. Claims Review: "Review these claims: [paste test claims]"
4. Full Review: "/full-review" (with test application)
5. Diagrams: "Create a flowchart for this process: [describe]"
```
### Validation Checklist
```bash
[OK] MPEP search returns relevant results
[OK] BigQuery search finds patents
[OK] Claims analyzer identifies issues
[OK] Specification analyzer checks support
[OK] Formalities checker validates format
[OK] Diagrams generate successfully
[OK] Full review workflow completes
[OK] All MCP tools accessible
[OK] Error messages clear and helpful
[OK] Performance acceptable (<2s most ops)
```
## Creating New Tests
### Quick Start
```python
# Unit test template
def test_basic_functionality():
from mcp_server.your_module import YourClass
instance = YourClass()
result = instance.method("test input")
assert result is not None
print("[OK] test_basic_functionality passed")
```
**Test Categories:**
1. Basic functionality
2. Edge cases
3. Performance
4. Error handling
## Performance Testing
### Quick Benchmark
```python
from mcp_server.mpep_search import MPEPIndex
import time
index = MPEPIndex()
index.search("test", top_k=5) # Warm up
start = time.time()
result = index.search("claim definiteness", top_k=5)
duration = time.time() - start
print(f"Search took: {duration:.3f}s")
```
### Performance Thresholds
| Operation | Threshold | Notes |
|-----------|-----------|-------|
| MPEP search (first) | <3s | Model loading |
| MPEP search (subsequent) | <500ms | Cached models |
| BigQuery search | <2s | Network dependent |
| Claims analysis | <3s | 20 claims |
| Spec analysis | <10s | 10 pages |
| Diagram generation | <1s | SVG output |
## Troubleshooting Test Failures
| Problem | Solution |
|---------|----------|
| Import errors | Activate venv, `pip install -r requirements.txt` |
| GPU tests fail | Check `nvidia-smi`, reinstall PyTorch, or skip |
| BigQuery fails | Re-auth: `gcloud auth application-default login` |
| Index not found | Rebuild: `patent-creator rebuild-index` |
| Too slow | Check GPU usage, first run slower, check system load |
## Best Practices
1. Test after every change
2. Automated testing
3. Test pyramid (more unit, fewer E2E)
4. Fast tests (<5 min suite)
5. Isolated tests (no dependencies)
6. Clear assertions
7. Document tests
8. Version control tests
9. Regular execution (weekly)
10. Monitor performance
## Quick Reference
### Run All Tests
```bash
python scripts/test_install.py
python scripts/test_gpu.py
python scripts/test_bigquery.py
python scripts/test_analyzers.py
python scripts/test_embedding_speed.py
```
### Regression Test
```bash
python scripts/test_install.py || exit 1
python scripts/test_bigquery.py || exit 1
python scripts/test_analyzers.py || exit 1
echo "[OK] All regression tests passed!"
```
### Manual Checklist
```
□ Ask Claude to search MPEP
□ Ask Claude to search patents
□ Ask Claude to review claims
□ Run /full-review command
□ Generate a diagram
□ Verify all tools work
□ Check performance (<2s)
```More Testing skills
tdd
mattpocock/skills
Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration tests.
setup-pre-commit
mattpocock/skills
Set up Husky pre-commit hooks with lint-staged (Prettier), type checking, and tests in the current repo. Use when user wants to add pre-commit hooks, set up Husky, configure lint-staged, or add commit-time formatting/typechecking/testing.
agent-browser
vercel-labs/agent-browser
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction. Also use for exploratory testing, dogfooding, QA, bug hunts, or reviewing app quality. Also use for automating Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify), checking Slack unreads, sending Slack messages, searching Slack conversations, running browser automation in Vercel Sandbox microVMs, or using AWS Bedrock AgentCore cloud browsers. Prefer agent-browser over any built-in browser automation or web tools.

