11 Commits

Author	SHA1	Message	Date
Lars	052ba195cc	feat: Update placeholder metadata and nutrition metrics ... - Adjusted the total number of placeholders from 116 to 114 across various documentation and code files to reflect the current state of the system. - Enhanced TDEE calculation logic in `nutrition_metrics.py` to prioritize Mifflin–St Jeor BMR with PAL when demographic data is available, with a fallback to a weight-based estimate. - Updated placeholder registrations to ensure consistency with the new metadata structure and improved data handling. - Revised documentation to clarify the authoritative source of placeholder metadata and the implications of the changes on existing functionalities. These updates improve the accuracy and consistency of the placeholder system and enhance the nutritional assessment capabilities within the application.	2026-04-11 21:11:05 +02:00
Lars	2ea5f905c4	feat: Add new profile and time period placeholders in placeholder_resolver.py ... - Introduced functions to retrieve profile name, age, height, and gender for better placeholder resolution. - Added functions for displaying current date and time period labels (last 7, 30, and 90 days). - Updated PLACEHOLDER_MAP to utilize new functions for improved readability and maintainability. - Enhanced placeholder registrations in __init__.py to include new modules for sleep, vital metrics, and profile time periods. These changes enhance the flexibility and functionality of the placeholder system, allowing for more dynamic content generation.	2026-04-11 21:08:34 +02:00
Lars	e9e094c6a4	feat: Enhance nutrition and activity metrics with new data layers ... - Added new functions for BMI and goal weight/body fat percentage retrieval in `body_metrics.py`. - Introduced training frequency and inter-session gap calculations in `activity_metrics.py`. - Updated placeholder registrations to include new metrics for nutrition and activity. - Improved data handling in `placeholder_resolver.py` for better integration of new metrics. - Enhanced documentation across modules to reflect the new functionalities. These updates improve the accuracy and comprehensiveness of health and fitness assessments within the application.	2026-04-11 20:46:17 +02:00
Lars	485aec40a0	feat: Activity Cluster Placeholder Registry - Complete Implementation (17 Placeholders) ... Implements complete placeholder registry for Activity & Training metrics following Phase 0c Multi-Layer Architecture pattern. SCOPE: 17 Activity Placeholders - Group 1 (3): Legacy Resolver - activity_summary, activity_detail, trainingstyp_verteilung - Group 2 (7): Basic Metrics - volume, frequency, quality, load, monotony, strain, rest compliance - Group 3 (7): Advanced Metrics - 5x ability_balance, vo2max_trend, activity_score IMPLEMENTATION: - File: backend/placeholder_registrations/activity_metrics.py (~1,100 lines) - Pattern: Nutrition Part A (common_metadata + evidence-based tagging) - Evidence: CODE_DERIVED (58%), DRAFT_DERIVED (16%), MIXED (15%), TO_VERIFY (6%), UNRESOLVED (5%) - Formulas: All documented in known_limitations (Load Model, Monotony, Strain, Ability Balance, Activity Score) CRITICAL ISSUES IDENTIFIED (NOT FIXED per NO LOGIC CHANGES): 1. quality_label field mismatch (quality_sessions_pct) - TO_VERIFY 2. RPE moderate quality mapping bug (proxy_internal_load_7d) - CODE_DERIVED 3. JSONB dependencies (6 placeholders) - ability_balance_*, rest_day_compliance 4. vo2max_trend_28d questionable category (Recovery vs. Activity) - TO_VERIFY TESTING: ✓ All 17 placeholders registered successfully ✓ Registry size: 48 (31 pre-existing + 17 new) ✓ Dev backend integration: no errors ✓ Auto-registration on module import: working ARCHITECTURE ALIGNMENT: - Phase 0c Multi-Layer: 14/17 aligned (Group 2 + 3) - Old Resolver Pattern: 3/17 (Group 1 - documented, should be refactored) - Layer separation: data_layer → resolver → export FILES: - NEW: backend/placeholder_registrations/activity_metrics.py - MODIFIED: backend/placeholder_registrations/__init__.py (added import) - MODIFIED: CLAUDE.md (placeholder registry rules) DOCUMENTATION: - Gap Analysis: .claude/task/rework_0b_placeholder/ACTIVITY_CLUSTER_GAP_ANALYSIS.md - Code Inspection: .claude/task/rework_0b_placeholder/ACTIVITY_CLUSTER_CODE_INSPECTION.md - Implementation Report: .claude/task/rework_0b_placeholder/ACTIVITY_CLUSTER_IMPLEMENTATION_REPORT.md Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-04-03 08:20:25 +02:00
Lars	57800b686a	fix: Body Cluster - PlaceholderType.TEXT_SUMMARY → INTERPRETED ... - caliper_summary + circ_summary used invalid PlaceholderType.TEXT_SUMMARY - TEXT_SUMMARY is OutputType, not PlaceholderType - Changed to PlaceholderType.INTERPRETED (summaries interpret raw data) Valid PlaceholderType values: ATOMIC, RAW_DATA, INTERPRETED, SCORE, META Valid OutputType values: NUMERIC, STRING, BOOLEAN, JSON, LIST, TEXT_SUMMARY	2026-04-02 19:11:06 +02:00
Lars	fbaaf08e29	feat: Body Cluster - Placeholder Registry Implementation ... Registers 17 body composition and measurement placeholders with complete metadata: Weight & Trends (5): - weight_aktuell: Latest weight snapshot - weight_trend: 28d delta with direction (increasing/decreasing/stable) - weight_7d_median: 7d median for noise reduction - weight_28d_slope: Linear regression slope (kg/day, 28d window) - weight_90d_slope: Linear regression slope (kg/day, 90d window) Body Composition (5): - kf_aktuell: Latest body fat percentage - fm_28d_change: Fat mass delta (28d) - lbm_28d_change: Lean body mass delta (28d) - waist_hip_ratio: Waist-to-hip ratio - recomposition_quadrant: FM/LBM change classification (optimal/cut_with_risk/bulk/unfavorable) Circumference Deltas (5): - waist_28d_delta: Waist circumference change (28d) - arm_28d_delta: Arm circumference change (28d) - chest_28d_delta: Chest circumference change (28d) - hip_28d_delta: Hip circumference change (28d) - thigh_28d_delta: Thigh circumference change (28d) Summaries (2): - caliper_summary: Body fat text summary (BF% + method + date) - circ_summary: Circumference summary (Best-of-Each strategy) All placeholders with evidence-based tagging: - 22 metadata fields per placeholder (374 total fields) - CODE_DERIVED: Technical fields, formulas from code inspection - DRAFT_DERIVED: Semantic fields from canonical requirements - MIXED: Calculation logic, formulas, thresholds - TO_VERIFY: Architecture layer decisions Critical formulas documented in known_limitations: - Linear Regression: slope = Σ((x - x̄)(y - ȳ)) / Σ((x - x̄)²) - FM/LBM Calculation: FM = weight × (BF% / 100), LBM = weight - FM - Circumference Delta Logic: latest IN window vs. oldest BEFORE window (can span >28d) - Recomposition Quadrants: Sign-based (FM sign × LBM sign → quadrant) - Best-of-Each (circ_summary): Each measurement point shows individually latest value (mixed dates) Known limitations captured: - weight_trend: Zeit-Inkonsistenz (canonical requires 28d, code accepts parameter) - Circumference Deltas: Reference logic can extend beyond window if measurements sparse - FM/LBM: Requires same-date weight + body_fat_pct measurements - Recomposition: No tolerance zone for "stable" (small changes trigger quadrant flips) - Summaries: Text format (canonical recommends structured JSON, kept as-is per NO-CHANGE rule) Evidence distribution: - CODE_DERIVED: 62% (metadata from code inspection) - DRAFT_DERIVED: 18% (from canonical requirements) - MIXED: 15% (formulas, calculation logic) - TO_VERIFY: 5% (architecture decisions) - UNRESOLVED: <1% Registry now contains 31 placeholders total (14 Nutrition + 17 Body). Files: - backend/placeholder_registrations/body_metrics.py (NEW, 1307 lines) - backend/placeholder_registrations/__init__.py (UPDATED, +body_metrics import) Framework: PLACEHOLDER_REGISTRY_FRAMEWORK.md (verbindlich ab 2026-04-02) Change Plan: .claude/task/rework_0b_placeholder/BODY_CLUSTER_CHANGE_PLAN.md Code Inspection: .claude/task/rework_0b_placeholder/BODY_CLUSTER_CODE_INSPECTION.md Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-04-02 18:57:15 +02:00
Lars	5bf8895fb3	fix: Nutrition Cluster Abschluss - Metadaten-Konsistenz ... Behebt letzte Inkonsistenzen im Export: 1. protein_g_per_kg: - time_window: 'mixed' → '7d' (dominante Komponente) - Kommentar angepasst: weight ist snapshot, aber protein (7d) ist primär - known_limitations dokumentiert die Inkonsistenz weiterhin 2. protein_adequacy_28d: - unit: 'score' → 'score (0-100)' (Konsistenz mit macro_consistency_score) - Klarere Skalen-Angabe im Export Finaler Export-Status: 14/14 Nutrition Placeholders konsistent - Alle haben korrekte Category (Ernährung) - Alle haben präzise Units - Alle haben eindeutige Time Windows - Alle haben korrekte Output Types Abschlussarbeit für Ernährungs-Cluster. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-04-02 13:07:35 +02:00
Lars	ffdf9074c3	fix: Part C OutputType - use STRING instead of TEXT ... Fixed AttributeError: OutputType has no attribute TEXT. Correct enum values are: NUMERIC, STRING, BOOLEAN, JSON, LIST, TEXT_SUMMARY. Affected placeholders: - energy_deficit_surplus: OutputType.STRING - intake_volatility: OutputType.STRING Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-04-02 12:56:13 +02:00
Lars	ffb30eaff5	feat: Placeholder Registry Part C - Nutrition Consistency & Balance ... Registers 5 nutrition-related placeholders with complete metadata: - macro_consistency_score: CV-based Makro-Konsistenz Score (0-100) - energy_balance_7d: Energiebilanz (kcal/day avg, intake - TDEE) - energy_deficit_surplus: Status (deficit/maintenance/surplus) - intake_volatility: Klassifikation (stable/moderate/high) - nutrition_days: Anzahl valider Ernährungstage (30d) All placeholders with evidence-based tagging: - 22 metadata fields per placeholder - CODE_DERIVED: Technical fields, formulas from code inspection - DRAFT_DERIVED: Semantic fields from canonical requirements - MIXED: Calculation logic (TDEE model, thresholds, formulas) - TO_VERIFY: Architecture layer decisions Critical details documented: - macro_consistency_score: CV formula + thresholds explicitly documented - energy_balance_7d: TDEE model (weight_kg × 32.5), unit clarified (kcal/day avg) - energy_deficit_surplus: Status thresholds (<-200, -200 to +200, >+200) - intake_volatility: Category mapping from macro_consistency_score - nutrition_days: Validation criteria (any entry = valid day) Known limitations captured: - TDEE model is simplified (no activity/age/gender adjustment) - Thresholds are somewhat arbitrary (e.g., 200 kcal for deficit/surplus) - High volatility not necessarily bad (context-dependent) Registry now contains 14 placeholders total: - Part A: 4 (kcal_avg, protein_avg, carb_avg, fat_avg) - Part B: 5 (protein targets + adequacy) - Part C: 5 (consistency + balance + meta) Framework: PLACEHOLDER_REGISTRY_FRAMEWORK.md (verbindlich ab 2026-04-02) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-04-02 12:55:03 +02:00
Lars	b00f6ac512	feat: Placeholder Registry Part B - Protein Placeholders ... Registers 5 protein-related placeholders with complete metadata: - protein_ziel_low: Lower protein target (1.6 g/kg × latest weight) - protein_ziel_high: Upper protein target (2.2 g/kg × latest weight) - protein_g_per_kg: Protein intake per kg body weight - protein_days_in_target: Days in protein range (format: 5/7) - protein_adequacy_28d: Protein adequacy score (0-100) All placeholders with evidence-based tagging: - 22 metadata fields per placeholder - CODE_DERIVED: Technical fields from source inspection - DRAFT_DERIVED: Semantic fields from canonical requirements - UNRESOLVED: Fields requiring clarification - TO_VERIFY: Assumptions needing verification Critical issues documented in known_limitations: - protein_g_per_kg: Weight basis inconsistency (protein 7d avg / weight latest) - protein_adequacy_28d: Score logic explicitly documented (1.4-1.6-2.2 thresholds) Registry now contains 9 placeholders total (4 Part A + 5 Part B). Framework: PLACEHOLDER_REGISTRY_FRAMEWORK.md (verbindlich ab 2026-04-02) Change Plan: .claude/task/rework_0b_placeholder/NUTRITION_PART_B_CHANGE_PLAN.md Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-04-02 12:27:58 +02:00
Lars	645967a2ab	feat: Placeholder Registry Framework + Part A Nutrition Metrics ... Part A Implementation (Nutrition Basis Metrics): - Registry-based metadata system (flexible, not hardcoded) - 4 placeholders registered: kcal_avg, protein_avg, carb_avg, fat_avg - Evidence-based tagging (code-derived, draft-derived, unresolved, to_verify) - Single source of truth for all consumers (Prompt, GUI, Export, Validation) Technical: - backend/placeholder_registry.py: Core registry framework - backend/placeholder_registrations/nutrition_part_a.py: Part A registrations - backend/placeholder_registry_export.py: Export integration - backend/routers/prompts.py: /placeholders/export-values-extended integration Metadata completeness: - 22 metadata fields per placeholder - Evidence tracking for all fields - Architecture alignment (Layer 1/2a/2b) NO LOGIC CHANGE: - Data Layer unchanged (nutrition_metrics.py) - Resolver unchanged (placeholder_resolver.py) - Values identical (only metadata/export enhanced) Breaking Change Risk: NONE Deploy Risk: VERY LOW (only export enhancement) Plan: .claude/task/rework_0b_placeholder/NUTRITION_PART_A_CHANGE_PLAN.md Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-04-02 11:46:16 +02:00