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Manually teach error pattern and solution to learning database.
Parse a user-provided "error -> solution" pair, classify it, store it in the cross-session learning database at high confidence, and confirm back. One pattern per invocation. All database operations go through the learning-db.py CLI.
Extract two fields from the user's input:
error_pattern: The error message or symptom textsolution: The fix or resolution textAccepted input formats:
/learn "error pattern" -> "solution"/learn "error pattern" => "solution"Both fields must be non-empty. If either is missing, ask the user for the missing part before proceeding. If the error pattern is vague (e.g., "it broke") or the solution is non-actionable (e.g., "fix it"), ask the user to provide the specific error message and concrete fix steps — vague patterns fail to match future errors and waste database space.
Determine fix_type and fix_action from the solution text by applying these rules in order:
npx skills add notque/vexjoy-agent --skill learnHow clear and easy to understand the SKILL.md instructions are, rated from 1 to 5.
Clear and well structured, with only minor parts that might need a second read.
How directly an agent can act on the SKILL.md instructions, rated from 1 to 5.
Mostly actionable with clear steps; only a few small gaps remain.