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name, description, disable-model-invocation
name description disable-model-invocation
level-up Gauge the user's technical + product knowledge through 7 adaptive questions, log verbatim answers with honest ratings, and grow a learning plan from the gaps found. Use when the user says "level up", "level-up session", "quiz me", "gauge my knowledge", or wants a new assessment round. Differentiator: this finds and maps gaps; the `teach` skill delivers lessons on them. true

Level Up

Run a 7-question adaptive assessment to map what the user knows and doesn't, relevant to the current project. The output is two files future agents rely on.

Files (repo-relative)

  • notes/learning/david-knowledge.md — verbatim Q&A pairs + ratings, one section per question, rounds appended.
  • notes/learning/LEARNING-PLAN.md — one concise bullet per genuine gap found.

State-check first: read both files in full if they exist. If previous rounds exist, pick mostly-new territory and calibrate starting difficulty to the recorded level. If missing, create the folder and both files (plan starts as just a header).

Question rules

  • 7 questions, strictly one at a time, plain text — never the questions UI.
  • Start easy, adapt difficulty each answer: good answer → harder, weak answer → sideways or down.
  • Orchestrator level only: systems, architecture, failure modes, security, data, scaling, product strategy, unit economics. NEVER syntax or code trivia — the user architects via AI agents, they don't write code.
  • Anchor questions in the current project's real stack and features. When a question touches real code, read it and show the actual snippet when teaching.
  • Cover different territory across rounds (e.g. round 1: request flow, DB, billing, moats; round 2: deploys, testing, incidents, data modeling, AI engineering, webhook security, cost engineering).

After every single answer

  1. Rate honestly 1-10. No flattery — the user wants calibration, not comfort.
  2. Say concisely what was missed or wrong, and teach the correct concept in a few sentences.
  3. Immediately save the verbatim answer + rating + gap notes to david-knowledge.md.
  4. If a genuine gap surfaced, append one concise bullet to LEARNING-PLAN.md. Skip minor misses.
  5. If the user pushes back on a rating ("I knew that, just didn't say it"), bump only if genuinely deserved, and record the bump with its reason.
  6. When the user says he has since learned a plan item, mark its bullet: strikethrough + ✓ learned YYYY-MM-DD.

After question 7

Append a final summary to david-knowledge.md: per-question ratings, overall score, the recurring pattern across answers (e.g. "architecture instincts ahead of failure-mode instincts"), strengths to build on, and gaps added. Give the user the same summary in chat, concise.