Suggest Patterns

Suggest Patterns

Mines tool failure history to suggest new patterns for memory.

Inputs

None. Runs analysis on existing failure data.

Workflow

1. Load Existing Patterns

• memory_read("learned/patterns") — existing error_patterns
• Count existing, list pattern names

2. Mine Patterns from Failures

• Read memory/learned/tool_failures.yaml
• Or use scripts/pattern_miner.py if available: mine_patterns_from_failures()
• Group similar errors, suggest when frequency ≥ 5
• Output: pattern, frequency, recommended_category, tools, example errors

3. Build Output

For each suggestion (top 10):

• Pattern name
• Frequency
• Recommended category
• Tools affected
• Example errors
• To add: skill_run("learn_pattern", '{"pattern": "...", "category": "...", "meaning": "...", "fix": "...", "commands": ["..."]}')

If no suggestions: "No new patterns to suggest! All common errors (5+) already captured."

4. Log

• memory_session_log("Ran pattern discovery", "Found X new patterns, existing: Y")

Key MCP Tools

• memory_read — learned patterns
• memory_session_log — session logging
• File read: memory/learned/tool_failures.yaml
• Optional: scripts/pattern_miner.py for mining logic

Chaining

• Chains to: learn_pattern — save suggested patterns