- Revised the status in the Capability Catalog to reflect partial implementation (M3).
- Added a new reference to `MEMBERSHIP_RBAC_DECISIONS_2026-06.md` in both the Capability Catalog and Club Membership documentation.
- Enhanced the Club Membership documentation with details on product decisions and onboarding phases.
- Implemented middleware in the backend to restrict access for unverified users and those pending club membership.
- Updated versioning in `version.py` to reflect changes in account lifecycle management.
- Enhanced the ACCESS_LAYER_AND_GOVERNANCE_PLAN.md with new specifications for capability documentation and community features.
- Added references to new documents detailing capability IDs and club membership features.
- Updated MULTI_TENANCY_RBAC_ARCHITECTURE.md to include links to the new specifications.
- Marked certain features as deprecated in backend/auth.py, indicating migration paths for club feature access.
- Incremented DB_SCHEMA_VERSION to 20260606078 in version.py to reflect recent changes.
- Introduced a new admin user content management endpoint for superadmins, allowing for moderation of user-generated content.
- Updated the backend to include new API functions for retrieving, patching, and deleting user content items.
- Enhanced the frontend with a new Admin User Content page and navigation link for easy access to user content management.
- Updated access layer documentation to reflect the new endpoint and its exempt status.
- Incremented version to 0.8.191 and updated changelog to document these additions in admin functionality.
- Introduced path reordering functionality using LLM with `ordered_step_indices`, allowing for dynamic adjustment of exercise progression paths.
- Added AI gap filling capabilities, enabling the system to propose new exercises when unbridgeable gaps are detected.
- Updated the backend to support new request parameters for path reordering and AI gap filling.
- Enhanced frontend components to reflect these new features, including alerts for AI proposals and adjustments in exercise display.
- Incremented version to 0.8.187 and updated changelog to document these significant enhancements in planning AI functionality.
- Introduced new functions to load exercise goals and variant names in chunks, improving data retrieval efficiency.
- Integrated semantic scoring into the ranking logic, allowing for more nuanced exercise suggestions based on semantic relevance.
- Updated the planning exercise suggestion process to include semantic brief handling, enriching the context for exercise recommendations.
- Adjusted the retrieval phase to incorporate dynamic retrieval weights based on semantic strength, enhancing the overall suggestion accuracy.
- Incremented version to 0.8.186 and updated changelog to reflect these significant enhancements in planning AI functionality.
- Incremented version to 0.8.185, reflecting the implementation of Phase C3 features.
- Introduced the `POST /api/planning/progression-path-suggest` endpoint for generating exercise progression paths.
- Enhanced the ExerciseProgressionGraphPanel with a new ExerciseProgressionPathBuilder for reviewing and saving paths.
- Updated changelog to document the new capabilities in planning AI functionality.
- Incremented version to 0.8.184, reflecting the implementation of Phase C2 features.
- Added support for displaying variant lists and suggested variant names in exercise suggestions.
- Enhanced the ExercisePickerModal to allow selection of exercise variants and improved handling of variant IDs.
- Updated backend logic to enrich planning hits with variant metadata, ensuring accurate exercise variant selection.
- Documented changes in the changelog to highlight the new capabilities in planning AI functionality.
- Incremented version to 0.8.183, reflecting the implementation of Phase C1 enhancements.
- Added support for progression graph auto-matching and variant-aware successors in exercise suggestions.
- Updated request and response structures to include `anchor_exercise_variant_id`, `progression_graph_name`, and `suggested_variant_id`.
- Enhanced frontend components to integrate planning AI search capabilities, including a new modal for exercise creation and improved context display in the exercise list.
- Updated changelog to document these significant improvements in planning AI functionality.
- Implemented a maximum of 3 exercises per preview request to prevent Gateway-504 errors, improving the stability of the exercise enrichment process.
- Adjusted batch sizes for applying exercises and previewing to optimize performance and resource management.
- Updated the frontend to reflect changes in preview handling, including user notifications about chunk sizes and potential timeouts.
- Incremented version to 0.8.180 and updated changelog to document these enhancements and fixes.
- Introduced the `exercise_enrichment_admin` API for batch exercise enrichment, allowing superadmins to filter candidates, preview, and apply skills.
- Updated the access layer documentation to include the new endpoint and its exempt status.
- Enhanced the frontend with a new admin page for exercise enrichment and updated navigation to include this feature.
- Incremented version to 0.8.179 and updated changelog to reflect these additions and improvements.
- Introduced the Scenario Pipeline for planning exercises, allowing for more nuanced query handling and exercise suggestions based on user intent.
- Enhanced the `suggestPlanningExercises` API to include `include_llm_intent`, `scenario_kind`, and `query_intent_summary`, improving the context provided to the frontend.
- Updated the `ExercisePickerModal` to display new information related to query intent and scenario classification, enhancing user experience during exercise selection.
- Incremented application version to 0.8.171 and updated changelog to document the new features and improvements in the planning AI capabilities.
- Implemented optional LLM-Rerank functionality in the planning exercise suggestion process, allowing for improved exercise ranking based on user-defined criteria.
- Updated the `suggestPlanningExercises` API to accept `planned_exercise_ids` for client-side overrides, enhancing flexibility in exercise selection.
- Enhanced the `ExercisePickerModal` to reflect LLM ranking status and support new planning context features.
- Incremented application version to 0.8.170 and updated changelog to document the new features and improvements in the planning AI capabilities.
- Implemented Phase 1.1 of the planning exercise suggestion functionality, integrating `ExerciseMatchProfile` and `PlanningTargetProfile` for improved exercise scoring based on profile dimensions.
- Updated the `suggestPlanningExercises` API to include a new `retrieval_phase` and `target_profile_summary`, enhancing the context provided to the frontend.
- Enhanced the `ExercisePickerModal` to display additional information from the planning target profile, including focus areas and top skills, improving user experience during exercise selection.
- Incremented application version to 0.8.169 and updated changelog to reflect the new features and improvements in the planning AI capabilities.
- Added new planning AI functionality with the introduction of the `suggestPlanningExercises` API endpoint for context-based exercise suggestions.
- Enhanced `ExercisePickerModal` to utilize planning context, allowing for a more tailored exercise selection experience.
- Updated `TrainingUnitEditPage` to pass planning context to the exercise picker, improving integration with the new planning features.
- Incremented application version to 0.8.167 and updated changelog to reflect the new planning AI capabilities and related enhancements.
- Added `exercise_instruction_rewrite` functionality to enhance AI-generated instructions, incorporating fields for goal, execution, preparation, and trainer notes.
- Updated `ExerciseFormAiPromptContext` to include new fields and methods for instruction handling.
- Enhanced the `run_exercise_form_ai_suggestion` function to support instruction rewriting and validation.
- Modified API endpoints and frontend components to integrate instruction features, including a new button for AI instruction revision.
- Incremented application version to 0.8.163 and updated changelog to reflect these changes, including migration details and new functionality.
- Introduced `ExerciseFormAiPromptContext` for unified handling of prompt-related data, enhancing the admin preview and exercise API.
- Added `run_exercise_form_ai_suggestion` function to streamline AI suggestion processing, integrating with the OpenRouter.
- Updated various modules to utilize the new context model, improving code clarity and reducing redundancy.
- Incremented application version to 0.8.162 and updated changelog to reflect these changes, including migration details and new functionality.
- Added `openrouter_model` field to the `ai_prompts` table, allowing for optional model overrides per prompt.
- Updated the `exercise_ai` module to utilize the effective OpenRouter model based on prompt-specific settings, enhancing flexibility in AI interactions.
- Enhanced the admin interface to support OpenRouter model configuration for prompts, improving usability for Superadmins.
- Incremented application version to 0.8.161 and updated changelog to reflect these changes, including migration details and new functionality.
- Introduced `load_and_render_ai_prompt` and `render_ai_prompt_template_for_row` in `ai_prompt_runtime` to streamline prompt loading and rendering processes.
- Added `AiPromptUnavailableError` for better error handling when prompts are inactive or missing.
- Created `ai_prompt_job` module with `ExerciseFormAiPromptContext` and `resolve_exercise_form_variables` to support admin preview functionality.
- Updated documentation and target architecture to reflect changes in the AI prompt system.
- Incremented application version to 0.8.160 and updated changelog accordingly.
- Added the `matrix_editor` endpoint to the ACCESS_LAYER_ENDPOINT_AUDIT.md, specifying its access requirements and exempt status for superadmins.
- Updated comments in the `matrix_editor.py` file to clarify its role as a superadmin tool and its access restrictions.
- Included the `matrix_editor.py` in the EXEMPT_ROUTERS list in the access layer hints script, ensuring proper access control documentation.
- Added a new target architecture document for the AI Prompt System, detailing context types, composition, and planning phases.
- Refactored the backend to utilize a shared function for loading AI prompt rows, reducing SQL duplication in the `exercise_ai` module.
- Incremented the application version to 0.8.159 and updated the changelog to reflect these changes, including enhancements to the AI prompt management and documentation links.
- Incremented version to 1.1 and updated the status to reflect the implementation of core features including `ai_prompts`, `prompt_resolver`, and the Superadmin HTTP API.
- Documented the current API endpoints for managing AI prompts, including CRUD operations and preview functionality.
- Introduced a new placeholder catalog and preview capabilities for the Superadmin interface.
- Enhanced the backend with new functions for handling AI prompt templates and integrated them into the API.
- Updated frontend components to include navigation and routing for the new Admin AI Prompts page.
- Incremented application version to 0.8.158 and updated changelog to reflect these changes.
- Added documentation for the new Superadmin CRUD endpoints for managing AI Skill Retrieval Profiles (`/api/admin/ai-skill-retrieval-profiles*`).
- Updated the ACCESS_LAYER_ENDPOINT_AUDIT.md to include the new Superadmin API and its exempt status.
- Registered the ai_skill_retrieval_admin router in the backend and updated versioning to reflect the changes.
- Enhanced the frontend with a new Admin page for AI Skill Retrieval, including navigation and API integration for profile management.
- Introduced migration 068 for `ai_skill_retrieval_profiles`, enabling configurable weights and quotes for skill catalog prioritization in exercise AI suggestions.
- Updated the `POST /api/exercises/ai/suggest` endpoint to include an optional `focus_areas_context` field, allowing for enhanced context in AI-generated suggestions.
- Enhanced the `exercise_ai` module to utilize context-based skill selection, incorporating scoring, category caps, and keyword patches for improved AI responses.
- Updated the ExerciseFormPageRoot component to pass focus area context to the AI suggestion API, streamlining user interaction with AI-generated content.
- Incremented version numbers in `backend/version.py` to reflect the latest changes and ensure accurate tracking in the changelog.
- Updated the AI Exercise Implementation Plan to include a detailed description of the new suggestion dialog for AI proposals, allowing users to preview and selectively adopt AI-generated summaries and skills.
- Implemented a new preview feature in the ExerciseFormPageRoot component, enabling users to review AI suggestions before applying them to the form.
- Enhanced the skill management process by normalizing AI-suggested skills and integrating them into the exercise form, improving user interaction and data handling.
- Incremented the version number from 0.2 to 0.3 in the AI Training Planning document to reflect the latest changes.
- Added a new reference to the `working/AI_PLANNING_KI_MULTISTAGE_FORECAST.md` document, outlining the architecture preview for the planning AI.
- Updated the changelog in `backend/version.py` to include the latest version entry, ensuring accurate tracking of changes.
- Updated the exercise form to include a tabbed navigation structure, improving user experience with sections for Stammdaten, Anleitung, Einordnung, Varianten, and Medien & Mehr.
- Introduced the concept of **Freigabelevel** (visibility level) in the UI, replacing previous terminology for clarity and consistency across components.
- Implemented new AI endpoints for exercise suggestions and regeneration, allowing for dynamic content generation without direct database writes.
- Removed the legacy `is_primary` flag from exercise skills in the UI, ensuring that intensity levels (`niedrig`, `mittel`, `hoch`) are the primary focus for skill management.
- Enhanced the variant management process with improved saving mechanisms and UI updates to reflect changes more intuitively.
- Added capabilities for weighted skill profiles, allowing trainers to compare training modules, frameworks, and regression paths based on skill contributions.
- Updated the skill scoring specification to include peer context separation and list filtering, ensuring accurate comparisons among visible artifacts of the same type.
- Enhanced the API to support batch summaries for skill profiles and discovery suggestions, improving data retrieval efficiency.
- Refactored frontend components to display skill metrics, including scores and peer percentages, with improved filtering options for better user experience.
- Updated documentation to reflect the latest changes and enhancements in the skill scoring system.
- Updated the skill scoring specification to include club-specific metrics and improved aggregation methods for skill profiles.
- Introduced new API endpoints for batch skill profile summaries, allowing for efficient retrieval of compact skill data.
- Enhanced frontend components to display skill profiles with club comparisons, improving user interaction and visibility of skill strengths.
- Added filtering options for skills in the framework programs, enabling users to refine selections based on training weight relative to club maximums.
- Improved CSS styles for skill profile displays, ensuring a cohesive and user-friendly interface across the application.
- Enhanced the skill scoring system with category grouping and a universal scale for improved comparability across programs.
- Introduced new calculations for artifact share percentage and universal percent, allowing for a more nuanced understanding of skill contributions.
- Updated the API to reflect changes in the skill profile structure, including main category and top skill details.
- Improved frontend components to display skills by main category, enhancing user experience in skill discovery and profile visualization.
- Adjusted tests to validate the new scoring logic and ensure accurate representation of skills and their weights.
- Enhanced the skill scoring formula to incorporate intensity and level range factors, improving the accuracy of skill contributions.
- Removed the use of `is_primary` and `development_contribution` from calculations, streamlining the scoring process.
- Updated documentation to reflect changes in the scoring logic and versioning.
- Adjusted frontend components to align with the new scoring criteria, ensuring consistent user experience across the application.
- Updated the framework program documentation to reflect the completion of Phase 3 v1.0, including new skill scoring and API enhancements.
- Added new API endpoints for skill profile retrieval and suggestions, improving the ability to aggregate and display skills based on training data.
- Introduced new UI components for skill profiles and discovery in the frontend, enhancing user interaction with training frameworks and skills.
- Updated version information to 0.8.151, reflecting the addition of skill profiles and related features.
- Added SQL aggregations for session duration (min/max) and goal titles in the training framework programs query.
- Updated the TrainingPlanningFrameworkImportModal component to include filtering options for focus areas, training types, and target groups.
- Implemented session duration display in the TrainingFrameworkProgramsListPage, improving user visibility of program details.
- Introduced utility functions for formatting session duration ranges, enhancing the overall user experience in training planning.
- Adjusted `PageFormEditorChrome` to set `showReturn` to false by default, making the back button optional.
- Removed `PageReturnButton` from `TrainingFrameworkProgramEditPage`, `TrainingModuleEditPage`, and `TrainingPlanTemplateEditPage` to streamline navigation.
- Updated documentation to reflect changes in editor actions and return context behavior for improved clarity.
- Replaced `PageReturnLink` with `PageReturnButton` for consistent back navigation across various pages.
- Updated multiple components, including `ExercisePeekModal`, `PageFormEditorChrome`, and `ExerciseDetailPage`, to utilize the new return context features.
- Enhanced CSS styles for the new return button to improve visual consistency.
- Improved navigation logic in `TrainingFrameworkProgramEditPage` and `TrainingModuleEditPage` to ensure seamless user experience when navigating back to previous locations.
- Introduced a new `PageReturnLink` component for consistent back navigation across pages.
- Updated `SaveSelectedExercisesAsModuleModal` and `SaveExercisesAsModuleModal` to utilize `navigateWithAppReturn`, preserving navigation context when redirecting after saving.
- Enhanced `TrainingModuleEditPage` and `TrainingUnitEditPage` with improved return context handling, allowing users to navigate back to their previous locations seamlessly.
- Added CSS styles for the new return link to improve visual consistency and user experience.
- Streamlined the section movement process by consolidating validation checks and enhancing the handling of parallel phase indices.
- Improved the overall clarity and efficiency of the section management functionality, ensuring a smoother user experience during edits.
- Updated CLAUDE.md and PROJECT_STATUS.md to reflect the latest app version (0.8.140) and database schema (20260515063) as of 2026-05-14.
- Enhanced DOMAIN_MODEL.md and PARALLEL_TRAINING_STREAMS_CONCEPT.md to clarify the implementation of phases and parallel streams in training units.
- Improved HANDOVER.md with detailed descriptions of the coaching and breakout functionalities, including rejoin logic and session management.
- Updated FACHLICHE_NUTZERFUNKTIONEN.md to include new features related to training planning and execution, emphasizing the integration of phases and parallel streams.
- Revised FEATURES_DELIVERED_2026-Q2.md to document the latest changes and improvements in the training framework and media management.
- Bumped APP_VERSION to 0.8.137 and updated the changelog to reflect recent changes.
- Introduced Migration 063 for training unit phases and parallel streams, enhancing the structure of training units.
- Updated the training planning API to support nested phases and sections, improving data retrieval for UI components.
- Enhanced section handling to accommodate new phase and stream structures, ensuring compatibility with existing workflows.
- Updated the backend to improve the fetching and insertion of training unit sections, including a new function for handling section items.
- Added documentation notes regarding the unique constraint on `training_unit_sections` and the implications for parallel training streams.
- Updated frontend components and utility functions to reflect changes in the training planning API and to prepare for future enhancements related to parallel streams.
- Bumped APP_VERSION to 0.8.122 and updated the changelog to reflect new features.
- Integrated useExerciseListCatalogsAndQuery hook in ExercisesListPage for improved exercise list management and data fetching.
- Enhanced documentation to include new concepts for parallel training streams and their technical specifications.
- Updated DOMAIN_MODEL and related technical specs to clarify the structure and functionality of training streams within units.
- Implemented a new API endpoint for retrieving dashboard KPIs, providing a consolidated overview of drafts, personal exercises, and year-to-date completed units.
- Updated the Dashboard component to utilize the new endpoint, enhancing data retrieval efficiency and user experience.
- Added a helper function in the exercises router for programmatic access to exercise listings.
- Updated versioning and changelog to reflect the addition of the dashboard feature.
- Updated app version to 0.8.110 and database schema version to 20260512057, reflecting recent enhancements.
- Revised project status documentation to include new versioning and next steps for development.
- Enhanced the functional specification for training modules and combination exercises, detailing upcoming features and improvements.
- Improved technical specifications to align with the latest code changes, ensuring consistency across documentation.
- Introduced new UI elements for toast notifications and unsaved changes prompts to enhance user experience.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Updated app version to 0.8.109, reflecting recent improvements in combination exercise handling.
- Introduced `rep_series_count` for slot profiles, allowing for multiple series in `rep` and `manual` modes, enhancing flexibility in exercise configurations.
- Updated the CombinationMethodProfileEditor and CombinationCoachSlots components to support and display the new series count feature.
- Enhanced ExerciseFormPage to manage series count and intra-series pauses effectively, improving user experience.
- Documented changes in the changelog for better tracking of feature enhancements.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Updated app version to 0.8.106, reflecting recent improvements in combination exercise handling.
- Introduced `advance_mode` for slot profiles, allowing for flexible timing options (timed, repetitions, manual) in the CombinationMethodProfileEditor.
- Enhanced the CombinationCoachSlots component to display timing summaries based on the selected advance mode.
- Updated ExerciseFormPage to manage combination slots with new validation and user feedback for exercise selection.
- Documented changes in the changelog for better tracking of feature enhancements.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Updated app version to 0.8.104, reflecting recent improvements in combination exercise handling.
- Enhanced the CombinationMethodProfileEditor to support structured slot timing profiles without requiring JSON input from trainers.
- Introduced quick ratio presets for circuit and interval training methods, improving user experience in setting up training profiles.
- Updated documentation and changelog to reflect new features and integration details.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Updated app version to 0.8.102, reflecting recent enhancements in combination exercises.
- Introduced structured method profiles for combination exercises, allowing for detailed planning and coaching support.
- Enhanced frontend components to display method profiles in the Exercise and Combination Coach views.
- Updated documentation to include new specifications and implementation details for method archetypes and profiles.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Added new API endpoints for managing training modules, including listing, creating, updating, and deleting modules.
- Implemented the ability to apply training modules to training units, allowing users to copy module content into specific sections.
- Enhanced the frontend with new pages for managing training modules and integrated modal functionality for applying modules within the training planning page.
- Updated version to 0.8.97 and adjusted database schema version accordingly.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Updated project status to version 0.8.96 as of 2026-05-12, reflecting recent enhancements and features.
- Added a new section for the user overview in `docs/FACHLICHE_NUTZERFUNKTIONEN.md`, providing a compact perspective for design and product teams.
- Revised references in various documents to include the new user overview and updated project status.
- Enhanced the requirements documentation to link to the user overview for better clarity.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Incremented application version to 0.8.64 and updated changelog with new features.
- Implemented inline media support in Rich Text Editor, allowing for drag-and-drop functionality and auto-scrolling.
- Enhanced media handling with a modal picker for media insertion, size selection, and improved user experience.
- Updated documentation to reflect changes in media handling and inline media specifications.
- Adjusted various API specifications to support new inline media features.
- Added functionality for inline media references in exercise text using `{{exerciseMedia:id}}` syntax, which normalizes to a canonical `<span>` element.
- Updated the frontend to utilize `ExerciseRichTextBlock` for rendering exercise content, allowing for embedded media display.
- Enhanced the Rich Text Editor to support inserting inline media placeholders.
- Version bump to 0.8.60 to reflect these changes in media handling and exercise content management.
