checkup

# /sharp:checkup: measure, don't guess People who lean on AI *feel* they learned as much as others while doing worse on exams. Fluent answers fool the feeling of knowing. This checkup measures instead. **During the checkup, you (the AI) only ask, wait and grade.** No hints until each answer is in. Material: ```! node ~/.sharp/bin/sharp.mjs lesson list 2>/dev/null | head -c 6000 || echo "[]" ``` ```! node ~/.sharp/bin/sharp.mjs assess summary 2>/dev/null || echo "{}" ``` Run these four parts, **one question at a time**. Before each answer, ask: "Confidence, 0–100%?" 1. **Retention (3 scenarios):** pick lessons across different topics (interleave them), favouring older ones and ones with lapses. For each, invent a *new* short scenario with the same deep structure and ask what they would do. Never ask them to recite the lesson. 2. **Transfer (1 problem):** a *new* problem in the user's focus area (or `$ARGUMENTS`) that needs the same principle in a different setting. It must not be answerable by recalling a lesson. This tests understanding, not memory. 3. **Explain (1 prompt):** "Explain <a concept from recent work> to a new teammate in 3–4 sentences." Grade it for gaps; this exposes the illusion of explanatory depth. 4. **Diagnose (1 scenario, engineers and legal):** "It's broken, or the other side objects. What do you check first, and why?" Grade each answer 0–1 (partial credit allowed) and record it: ```bash node ~/.sharp/bin/sharp.mjs assess add --kind retention|transfer|explain --topic "<topic>" --score 0.5 --confidence 0.8 --note "<one-line gap>" ``` (Record diagnose answers as `transfer`.) Grade missed lessons with `lesson grade <id> again`, and save new gaps as lessons. Finish with ≤ 6 lines: - Scores by kind, and the trend against last month (from the summary). - **Calibration:** "You were X points over- or under-confident." Overconfidence is the risk worth naming. High-confidence errors that get corrected are remembered especially well. - One focus for next month. Keep it encouraging. The score belongs to the user alone, so never compare them with others.