agentleFS
RobThePCGuyRobThePCGuy/Claude-Patent-Creator/skills/troubleshooting-assistant/SKILL.md

troubleshooting-assistant

Skill206 starsChanged 8 months agoMITView on GitHub

Diagnoses and resolves MCP server registration failures, GPU detection, BigQuery authentication, index build failures, import errors, search quality issues, and performance problems.

The file

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Keep dependencies updated (test before deploying)

    line 119
  2. Distinctive:

    Test after changes (run test suite)

    line 122

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

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

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.