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Manages testing lifecycle including unit tests, integration tests, validation, and quality assurance.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
| name | testing-assistant |
| description | Manages testing lifecycle including unit tests, integration tests, validation, and quality assurance. |
Expert system for testing and validating the Claude Patent Creator.
FOR CLAUDE: Test scripts in scripts/ directory.
Running test suites, validating new features, testing after changes, debugging failures, creating tests, setting up CI/CD, performance testing, E2E validation, regression testing.
/\
/ \ E2E (Manual + Automated)
/----\
/ API \ Integration Tests
/--------\
/ Unit \ Unit Tests
/----------\
Strategy: More unit tests (fast, isolated), fewer integration (moderate), minimal E2E (slow).
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:
python scripts/test_install.py
Test MCP tools through Claude Code interface.
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]"
[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)
# 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:
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")
| 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 |
| 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 |
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
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!"
□ 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)
End-to-end patent campaign from ANY raw material ("here is some information; make a patent") to a filing-ready provisional package - invention mining, worth-it economics (design-around cost, detectability), exhaustive adversarial prior art, claims-first drafting, machine-verified compliance, hostile-examiner attack pass, and an honest no-go when nothing clears the bar or the fence is not worth the money
Fast, cloud-based patent searching across 100 million+ worldwide patents using Google BigQuery - keyword search, CPC classification, patent details retrieval
Search 100M+ patents via the MCP server's BigQuery tools. No standalone scripts; everything goes through the MCP tools registered by the patent-creator server.
Systematic 7-step methodology for comprehensive patent prior art searches and patentability assessments using BigQuery and CPC classification
Search European patents using EPO OPS API (full-text, legal status, families) and BigQuery (100M+ patents, EP filter) for prior art, competitive intelligence, and freedom-to-operate analysis
Expert system for reviewing utility patent applications against USPTO MPEP guidelines.