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Troubleshooting Assistant

  • 43 installs
  • 167 repo stars
  • Updated August 2, 2026
  • robthepcguy/claude-patent-creator

Helps with ai & agent building tasks during AI-assisted development.

About

troubleshooting-assistant is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted coding.

  • troubleshooting-assistant
  • AI & Agent Building
  • AI-coding skill

Troubleshooting Assistant by the numbers

  • 43 all-time installs (skills.sh)
  • +1 installs in the week ending Jul 26, 2026 (Skillselion tracking)
  • Ranked #7,921 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 4, 2026 (Skillselion catalog sync)
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Listed on Skillselion
Installs43
repo stars167
Last updatedAugust 2, 2026
Repositoryrobthepcguy/claude-patent-creator

What it does

Helps with ai & agent building tasks during AI-assisted development.

Files

SKILL.mdMarkdownGitHub ↗

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(); \
           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_patents('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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