What problem does it solve? Learners practicing Object-Role Modeling with the barwise gym accumulate pass/fail records but lack guidance on interpreting them. This Skill reads those session logs and miss cards to answer "what do I keep getting wrong?" and "how do I get better?" with evidence-based coaching instead of guesswork. ## Core Features & Use Cases - Trend Analysis: Parses the tab-separated gym session log chronologically to distinguish one-off failures from recurring failure patterns across runs. - Bias Diagnosis: Maps recurring failure signatures (e.g., requires_verbalization, forbids_population) to the reductive-bias catalog, naming the underlying habit of thought such as table-thinking or attribute-first modeling. - Targeted Recommendations: Suggests the next exercises, readings, and proficiency-level transitions based on what the learner passes unaided, plus reminders to import miss cards into Anki. - Use Case: A learner has run barwise gym check a dozen times and keeps failing ternary decomposition exercises. This Skill identifies the recurring forbids_population signature, explains the binary-arity assumption behind it, and recommends the next exercise targeting that bias. ## Quick Start Ask the coach to review my barwise gym history and tell me what I keep getting wrong and which exercise I should try next.
