# GRIP Unified Five-Level Generation Template Every future category must generate exactly five questions per image in this order: 1. **Simple Description** — one directly visible fact; the easiest question available. 2. **Basic Relational** — one comparison or one-step rule application. 3. **Comparative/Structural** — reasoning across multiple elements, ranking, an extreme, or cross-referencing image regions. 4. **Compound Reasoning** — combine at least two facts or apply a multi-step formula/rule chain; do not use hypothetical framing. 5. **Extrapolative/Counterfactual** — apply an explicitly defined hypothetical geometric change, extrapolate a pattern, or justify why a result changes. The operation and answer must be deterministic and independently recomputable from raw stored scene geometry. ## Required question schema ```json { "question_id": "category_0001_q5", "question_text": "...", "question_type": "dataset_specific_operation", "ground_truth": "...", "answer_format": "...", "difficulty_level": 5 } ``` ## Acceptance checklist - Exactly five ordered levels `[1,2,3,4,5]` for every image. - Level 5 uses the image's actual stored parameters, not a generic unverifiable “what if.” - A separate validator re-derives every answer without reading it back as its source of truth. - Ambiguous counterfactuals are rejected during generation. - Metadata-only question regeneration must not modify PNG files. - Flattened outputs contain exactly 15,000 rows for a 3,000-image category. - `question_set.csv` excludes ground truth; `answer_key.csv` includes it. - No inference, scoring, model API, or evaluation harness is part of generation. ## Mandatory distribution reporting Every generation and validation report must automatically include: - min, p25, p50, p75, p95, and max for every sampled continuous parameter; - complete value counts for every sampled categorical parameter; - target-label association checks for all stored scene parameters, with target-defining quantities explicitly distinguished from nuisance features; - per-cause rejection counts and synthetic violating/boundary injection tests for every active guard. Reporting only parameters changed in the current development pass is not sufficient. This full dump is a standing requirement for all future GRIP categories so degenerate samplers and fix-induced correlations are visible in the same build that introduces them.