- Introduced new catalog context handling in planning prompt functions, allowing for improved integration of planning variables.
- Added optional catalog context parameters in various functions to streamline the merging of planning prompt variables.
- Updated frontend components to include CatalogPromptSlotsEditor for managing prompt slots across different catalog types.
- Enhanced API utilities to support fetching and updating catalog prompt slots, improving backend functionality for catalog management.
- Incremented version numbers and updated changelog to reflect the new features and improvements.
- Updated `PROJECT_STATUS.md` to reflect the implementation of F15 features, including the unified slot review and handling of `findings_stale`.
- Enhanced `PROGRESSION_GRAPH_SLOT_EDITOR_SPEC.md` with detailed descriptions of new functionalities related to the match dialog and path quality assessments.
- Introduced new functions in `exercise_progression_graphs.py` to validate exercise visibility against progression graph settings, ensuring proper governance.
- Improved frontend components to support new governance parameters (visibility and club_id) in exercise creation workflows.
- Updated documentation in `HANDOVER.md` and `PLANNING_KI_ROADMAP.md` to outline the latest developments and validation results for the F15 features.
- Enhanced utility functions for exercise creation to incorporate governance settings, improving the overall user experience in the path builder and editor.
- Introduced `_annotate_slot_diffs` to mark trivial ID swaps in slot differences, improving clarity in comparison results.
- Added `_actionable_slot_diffs` to filter out non-actionable differences, streamlining the evaluation process.
- Implemented `_build_rematch_suggestion_diffs` to generate suggestions based on rematch logs, enhancing the path optimization workflow.
- Updated `_build_progression_compare_response` to incorporate actionable slot differences and rematch suggestions, improving the response structure.
- Enhanced frontend components to display rematch suggestions and handle trivial differences more effectively.
- Bumped version to reflect the new features and improvements.
- Updated `PROJECT_STATUS.md` to reflect the addition of the Planning AI Progression Graph and its context in the roadmap.
- Enhanced `DOMAIN_MODEL.md` with details on the new `planning_catalog_context` features, allowing trainers to manage curriculum stages and context.
- Added tests in `test_planning_catalog_context.py` to validate the separation of LLM highlights from fix hints during QA processes.
- Updated `HANDOVER.md` and `PLANNING_KI_ROADMAP.md` to reflect the latest app version and improvements in the planning context.
- Enhanced frontend components to support the new planning catalog context, including updates to `ExerciseProgressionPathBuilder` and `ProgressionGraphEditor`.
- Bumped version to 0.8.233 to reflect the new features and improvements.
- Introduced multistage path quality assurance (QA) functionality to improve exercise relevance and feedback through structured tiers and optimization hints.
- Updated stage specifications to include `start_state` and `target_state` for better contextualization in roadmap matching.
- Enhanced semantic brief construction with technique sibling exclusions to refine exercise selection based on primary topics.
- Improved path retrieval logic to incorporate new parameters for nuanced matching against learning goals.
- Incremented application version to reflect these updates.
- Introduced `intent_context` and `semantic_brief` parameters in `try_llm_stage_specs` to improve context handling for stage specifications.
- Updated `build_goal_analysis` to extract explicit exclusions from goal queries, enhancing constraint management.
- Enhanced `roadmap_context_from_override` to enrich semantic briefs with path constraints and finalize stage specifications with intent context.
- Incremented application version to reflect these updates.
- Added `semantic_brief_for_stage` function to enhance semantic briefs with stage learning goals for improved roadmap matching.
- Introduced `exercise_passes_stage_learning_goal_gate` to validate exercises against stage learning goals, enhancing relevance checks.
- Updated path retrieval and scoring logic to incorporate stage learning goals, allowing for more nuanced exercise selection.
- Enhanced UI to indicate weak matches with stage learning goals, improving user feedback on exercise relevance.
- Incremented application version to reflect these updates.
- Updated the `CLAUDE.md` to reflect changes in the Progression Graph, including the new Ist-Stand and roadmap specifications.
- Enhanced `PLANNING_EXERCISE_SUGGEST_CONTEXT.md` with detailed descriptions of the current state and features of the planning exercise.
- Revised `PLANNING_PROGRESSION_ROADMAP_SPEC.md` to document the implementation status of various phases and their corresponding migrations.
- Incremented application version to 0.8.217 to incorporate recent updates and improvements in the planning context and roadmap functionalities.
- Introduced `roadmap_qa_mode` to manage QA behavior based on roadmap-first logic, improving gap detection between major steps.
- Updated `detect_path_gaps` to skip gaps for roadmap-planned neighbor pairs, enhancing the accuracy of path assessments.
- Added new helper function `is_roadmap_planned_neighbor_pair` to facilitate roadmap neighbor checks.
- Updated relevant tests to validate new functionality and ensure robustness.
- Incremented application version to 0.8.209 to reflect these changes.
- Added `planning_context` to the `suggestExerciseAi` endpoint, enabling structured planning context for new exercise creation.
- Updated relevant components and backend logic to handle the new planning context, enhancing the AI's exercise suggestion capabilities.
- Incremented application version to 0.8.208 to reflect these changes.
- Added support for editable major steps in the roadmap, allowing users to modify phase, learning goals, and order before exercise matching.
- Introduced a new `roadmap_override` feature to facilitate customized retrieval without re-invoking the roadmap AI.
- Updated the `ExerciseProgressionPathBuilder` component to incorporate these new features, enhancing user interaction and flexibility.
- Incremented application version to 0.8.207 to reflect these changes.
- Introduced a roadmap-first approach for retrieval, allowing for structured exercise suggestions based on stage specifications and major steps.
- Added functionality to generate gap-fill offers for unfilled roadmap stages, improving the relevance of exercise recommendations.
- Updated the `ExerciseProgressionPathBuilder` to support the new roadmap-first feature, enhancing user experience with clearer exercise paths.
- Incremented application version to 0.8.206 and updated the database schema version to reflect these changes.
- Introduced a roadmap-first approach for the planning AI, allowing for a structured progression graph that aligns with the overall project roadmap.
- Added new functionality to strip off-topic steps from exercise paths, improving the relevance of generated exercise suggestions.
- Implemented a detailed goal text generation for AI proposals, enhancing the context provided for new exercises.
- Updated the ExerciseProgressionPathBuilder component to support new features, including roadmap previews and improved focus area handling.
- Incremented application version to 0.8.205 and updated database schema version to 20260606086 to reflect these changes.
- Updated the capability catalog to reflect a registry-first approach, requiring modules to register rights and quotas upon implementation.
- Enhanced the backend to synchronize the rights registry with the database, ensuring only registered capabilities and features are displayed in the admin matrix.
- Modified SQL queries in the admin rights router to filter capabilities and features based on module registration.
- Updated documentation to clarify the new rights and features registry process, replacing the previous catalog-first method.
- Incremented application version to 0.8.201 and updated database schema version to 20260606084 to reflect these changes.
- Updated the Membership RBAC Decisions document to reflect the latest implementation status and roadmap, including new features and enhancements.
- Incremented application version to 0.8.200 and updated database schema version to 20260606083.
- Added a new API endpoint to clear capability grants for club roles, improving admin rights management.
- Enhanced the Admin Rights page in the frontend to display enforcement status and feature consumption details for capabilities.
- Improved the user interface for better clarity on rights and capabilities management.
- 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.
- 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.
- Updated APP_VERSION to 0.8.166 and modified BUILD_DATE to reflect recent changes.
- Enhanced AI exercise creation process with a new quick create feature, allowing users to generate exercises based on search input.
- Introduced a rich text editor for editing AI-generated drafts, improving user experience in exercise creation.
- Updated ExercisePickerModal and related components to support the new quick create functionality, including error handling and input validation.
- Added new utility functions for parsing search queries and building exercise payloads from drafts.
- 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.
- 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 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.
- Introduced detailed logging for AI operations in the `exercise_ai` and `openrouter_chat` modules, activated by the `SHINKAN_AI_DEBUG` environment variable, to aid in debugging and performance monitoring.
- Updated the `run_exercise_ai_suggestion` function to log prompt lengths, response sizes, and JSON parsing errors, enhancing transparency in AI interactions.
- Improved the `_flatten_message_content` function to handle nested content structures more effectively, ensuring compatibility with various AI response formats.
- Incremented the application version to 0.8.157 and updated the changelog to reflect these enhancements, including new logging features and content handling improvements.
- Added a new function `_first_balanced_json_array` to extract the first complete top-level JSON array from arbitrary text, enhancing robustness in parsing.
- Updated the `run_exercise_ai_suggestion` function to raise clear HTTP exceptions for empty responses from the OpenRouter, ensuring better error handling.
- Introduced `_flatten_message_content` in the `openrouter_chat` module to handle structured message content from OpenAI, improving compatibility with various content formats.
- Incremented the application version to 0.8.156 and updated the changelog to reflect these enhancements, including improved error messages and JSON parsing capabilities.
- 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 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.
- Added Vitest as a testing framework and included test scripts in package.json for improved testing capabilities.
- Refactored TrainingPlanningPageRoot component by removing unused state variables and imports, streamlining the code for better readability and performance.
- Introduced new utility functions for planning routes to enhance navigation within the training planning interface.
- 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 0.8.136 and updated the changelog to reflect recent changes.
- Fixed the Mandanten-Header handling in `api/exercises.js` for improved API requests.
- Continued Frontend Phase 4 with the addition of the `exercises.js` module, enhancing the API structure.
- Updated architecture documentation to include details on the new `exercises.js` API and its integration with the existing client structure.
- Enhanced `utils/api.js` to re-export the new exercises module, streamlining API access.
- Bumped APP_VERSION to 0.8.134 and updated the changelog to reflect recent changes.
- Continued Frontend Phase 4 with the introduction of the `frontend/src/api/planning.js` module for training planning.
- Updated architecture documentation to include details on the new `planning.js` API and its integration with the existing client structure.
- Enhanced `utils/api.js` to re-export the new planning module, streamlining API access.
- Bumped APP_VERSION to 0.8.133 and updated the changelog to reflect recent changes.
- Initiated Frontend Phase 4 Welle 1, introducing a centralized HTTP client in `frontend/src/api/client.js` while maintaining `utils/api.js` as a facade.
- Documented the changes in the architecture roadmap and README for clarity on the new API structure.
- Bumped APP_VERSION to 0.8.132 and updated the changelog to reflect recent changes.
- Removed unused imports and refactored the ExerciseFormPage, ExercisesListPage, and TrainingPlanningPage for improved code clarity and maintainability.
- Enhanced the overall structure of the components by eliminating redundant code and optimizing imports.
- Bumped APP_VERSION to 0.8.131 and updated the changelog to reflect recent changes.
- Added the TrainingPlanningUnitFormModal component to the TrainingPlanningPage for enhanced training unit management.
- Refactored frameworkLineageText utility function for better code organization and reusability in the training planning context.
- Updated BASELINE_SNAPSHOT documentation to include new metrics and logging details for k6 health checks.
- Bumped APP_VERSION to 0.8.121 and updated the changelog to reflect new features.
- Introduced the ExerciseListFilterModal and ExerciseListBulkModal components, enhancing the exercise list functionality.
- Modularized the ExerciseListPage to improve code organization and maintainability.
- Added Playwright tests for the filter dialog functionality, ensuring proper user interaction and visibility.
- Bumped APP_VERSION to 0.8.119 and updated the changelog to reflect new features.
- Introduced the ExerciseListCard component and implemented lazy loading for the Progression Tab using React's Suspense.
- Enhanced the ExercisePickerModal with virtualization for improved performance using @tanstack/react-virtual.
- Updated documentation to reflect the new app version and its corresponding changes.
- Bumped APP_VERSION to 0.8.118 and updated DB_SCHEMA_VERSION to 20260514062.
- Enhanced the dashboard API with a new endpoint that consolidates training home data, allowing for a single request to retrieve upcoming training sessions, planned sessions with notes, and review pending items.
- Updated the frontend Dashboard component to utilize the new API structure, improving data loading efficiency and user experience.
- Added migration details and changelog entries to reflect the latest changes and improvements.
- Bumped APP_VERSION to 0.8.117 and updated DB_SCHEMA_VERSION to 20260514061.
- Enhanced the training units API with optional keyset pagination, allowing for more efficient data retrieval.
- Updated the changelog to reflect the new features and improvements, including changes to the frontend API integration for training units.
- Adjusted documentation to align with the new app version and its corresponding changes.
- Bumped APP_VERSION to 0.8.116 and updated the changelog to reflect changes, including the implementation of a new loading strategy for the Org-Inbox that utilizes requestIdleCallback to optimize API calls during dashboard initialization.
- Updated documentation to reflect the new app version and its corresponding changes.
- Introduced a new job `k6-health-baseline` in the Gitea CI workflow to run health checks independently from Playwright tests, enhancing clarity and organization.
- Updated documentation to reflect the changes in the CI pipeline, specifying the execution order and purpose of each job.
- Adjusted environment variables and health check logic for both development and production modes, ensuring accurate testing conditions.
- Bumped APP_VERSION to 0.8.115 and updated the changelog to reflect changes, including the introduction of keyset pagination for the GET /api/exercises endpoint.
- Enhanced the exercises router to support cursor-based pagination using cursor_updated_at and cursor_id, improving performance and user experience.
- Updated frontend components to utilize the new pagination method, removing offset-based loading logic.
- Bumped APP_VERSION to 0.8.114 and updated DB_SCHEMA_VERSION to 20260514060.
- Added changelog entry for version 0.8.114, detailing migration 060 for exercise scaling and indexing improvements.
