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troubleshooting-assistant

troubleshooting-assistant

github.com/robthepcguyDevelopment20656 installsUpdated 2d ago
Repository

About troubleshooting-assistant

A diagnostic skill for identifying and resolving issues in Claude Patent Creator. It organizes troubleshooting across MCP server loading, GPU, BigQuery, indexes, dependencies, and configuration.

Key features

  1. 01Follow a structured diagnostic workflow
  2. 02Troubleshoot MCP server loading
  3. 03Diagnose GPU and BigQuery problems
  4. 04Resolve index and dependency errors
  5. 05Run health checks and isolate components

Use cases

  1. 01Investigate an MCP server that will not load
  2. 02Diagnose failed searches or authentication
  3. 03Address slow performance and index errors

MCP support

Covers MCP server loading and tool errors, including checks with `claude mcp list` and MCP communication debugging.

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/robthepcguy/claude-patent-creator --skill troubleshooting-assistant

After installing, type/troubleshooting-assistantin Claude Code to confirm it loaded.

Details

From the project README

Troubleshooting Assistant Skill

Expert diagnostic system for identifying and resolving Claude Patent Creator issues.

When to Use

System not working, error messages, slow performance, MCP server not loading, search returns no results/errors, GPU not detected, BigQuery auth fails, index build fails, tests failing, unexpected behavior.

Troubleshooting Methodology

Problem Reported
  |
[1] Gather Information (errors, recent changes, system state)
  |
[2] Reproduce Issue (minimal test case, consistent?)
  |
[3] Isolate Component (which part failing? dependencies?)
  |
[4] Diagnose Root Cause (check logs, test components, verify config)
  |
[5] Apply Fix (targeted solution, verify works)
  |
[6] Prevent Recurrence (document, add monitoring, update checks)

Common Issues & Quick Fixes

IssueQuick Fix
MCP server not loadingclaude mcp list -> Re-register if missing
GPU not detectedReinstall PyTorch with CUDA
BigQuery auth failsgcloud auth application-default login
Index not foundpatent-creator rebuild-index
Import errorsActivate venv: venv\Scripts\activate
Slow searchesCheck GPU usage, reduce top_k, disable HyDE
Irrelevant resultsRephrase query with MPEP terminology

Detailed Issue Guides

MCP Server Issues

Problems: Server not loading, tools don't work/return errors

  • 5-step diagnostic workflow
  • Path verification and correction
  • Dependency troubleshooting
  • Server restart procedures
GPU & BigQuery Issues

Problems: GPU not detected, slow performance, BigQuery auth fails, query timeouts

  • CUDA detection and PyTorch reinstallation
  • Performance diagnostics and optimization
  • BigQuery authentication and permissions
  • Timeout configuration
Index, Dependencies & Configuration

Problems: Index not found, build fails, ModuleNotFoundError, import errors, env vars not loading, irrelevant search results

  • Index rebuild procedures
  • OOM (Out of Memory) solutions
  • Virtual environment activation
  • Pydantic validation errors
  • Configuration troubleshooting
  • Search quality tuning

Diagnostic Tools

Health Check Suite
# Full system health
patent-creator health

# Individual components
python scripts/test_gpu.py
python scripts/test_bigquery.py
python scripts/test_analyzers.py
python scripts/test_install.py
Component Isolation
# Test MPEP search
python -c "from mcp_server.mpep_search import MPEPIndex; \
           index = MPEPIndex(); index.build_index(); \
           print('OK' if index.search('test', top_k=1) else 'FAILED')"

# Test BigQuery
python -c "from mcp_server.bigquery_search import BigQueryPatentSearch; \
           search = BigQueryPatentSearch(); \
           print('OK' if search.search_by_keywords('neural network', limit=1) else 'FAILED')"

# Test analyzers
python -c "from mcp_server.claims_analyzer import ClaimsAnalyzer; \
           analyzer = ClaimsAnalyzer(); \
           print('OK' if analyzer.analyze('1. A test claim.') else 'FAILED')"
  • Log analysis (debug mode)
  • MCP communication debugging
  • Performance profiling
  • Memory profiling
  • Issue escalation procedures

Best Practices for Prevention

  1. Regular health checks (weekly patent-creator health)
  2. Monitor logs for warnings/errors
  3. Keep dependencies updated (test before deploying)
  4. Backup before changes (especially index rebuilds)
  5. Document modifications
  6. Test after changes (run test suite)
  7. Version control (use git)
  8. Environment consistency (same Python/CUDA versions)

Quick Reference

Most Common Errors
ErrorCategorySolution
"Tool not found"MCPclaude mcp list
"ModuleNotFoundError"DependenciesActivate venv, reinstall
"CUDA not available"GPUReinstall PyTorch with CUDA
"Permission denied" (BigQuery)Authgcloud auth application-default login
"Index not found"Indexpatent-creator rebuild-index
"Out of memory"Index BuildReduce batch size
"Validation error"InputCheck Pydantic model parameters
Diagnostic Commands
# System health
patent-creator health

# Test components
python scripts/test_gpu.py
python scripts/test_bigquery.py
python scripts/test_install.py

# Check registration
claude mcp list

# Check paths
patent-creator verify-config

# Enable debug logging
export PATENT_LOG_LEVEL=DEBUG

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