- Introduced `build_progression_gap_snapshot` function to create a compact roadmap context for gap exercises, integrating start situation, target state, and stage specifications.
- Updated `build_gap_fill_goal_text` to include roadmap snapshot details, enhancing the context for AI-generated exercises.
- Enhanced `ProgressionPathSuggestRequest` and related components to support new structured inputs for start/target analysis, improving user experience and AI suggestions.
- Incremented application version to 0.8.212 to reflect these changes.
- Added `include_llm_start_target` option to `ProgressionPathSuggestRequest` for improved roadmap suggestions.
- Introduced new classes `StartTargetExtractArtifact` and `StartTargetResolveMeta` to handle LLM extraction results and metadata.
- Implemented `try_llm_start_target_extract` function to extract start and target states from goal queries using LLM.
- Updated `resolve_roadmap_structured_input` to prioritize user inputs, LLM extractions, and regex parsing for start/target resolution.
- Enhanced `ExerciseProgressionPathBuilder` to utilize new structured inputs and display extraction sources.
- Incremented application version to 0.8.211 to reflect these changes.
- Introduced `RoadmapStructuredInput` to encapsulate structured inputs for start situation, target state, and roadmap notes.
- Updated `ProgressionPathSuggestRequest` to include new fields for structured roadmap inputs.
- Implemented parsing logic for goal queries to extract start and target states, enhancing the goal analysis process.
- Enhanced `build_goal_analysis` to utilize structured inputs, improving the clarity and relevance of generated goals.
- Updated the `ExerciseProgressionPathBuilder` component to support new structured input fields, enhancing user experience.
- Incremented application version to 0.8.210 to reflect these changes.
- 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 logic to manage path capacity dynamically, allowing users to expand the maximum number of steps when inserting new offers.
- Implemented confirmation prompts for users when the path is full, enhancing user experience and decision-making.
- Updated the `ExerciseProgressionPathBuilder` component to reflect these changes, improving the handling of gap-fill offers and user interactions.
- Adjusted UI messages to clarify the implications of adding new steps and the conditions under which users can expand the path.
- 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.
- Introduced a new environment variable `CLUB_FEATURE_ENFORCE` to control club feature access, allowing values of 1, true, or yes for activation.
- Updated the backend logic to check for club feature enforcement, raising HTTP exceptions when access is denied without an active club context.
- Enhanced the admin rights router with a new endpoint to check the enforcement status of club features.
- Incremented application version to 0.8.202 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 the `consume_club_feature_with_usage` function to standardize feature consumption across endpoints, improving code reusability and clarity.
- Implemented `merge_feature_usage_into_response` to embed feature usage data in API responses, streamlining frontend integration.
- Updated various backend routers to utilize the new consumption logic, ensuring consistent feature usage tracking during AI-related actions.
- Enhanced tests to validate the new consumption and logging behavior.
- Incremented application version to 0.8.199 and updated module version for 'club_features' to 1.6.0 to reflect these changes.
- Replaced the admin club feature exemptions router with a new admin rights router to streamline capability management.
- Added new API endpoints for managing admin rights, including capability grants and quota bypass for portal roles and profiles.
- Updated the frontend to include navigation and lazy loading for the new Admin Rights page.
- Incremented application version to 0.8.197 to reflect these changes and enhancements.
- Added support for club feature quota bypass based on portal roles and profile grants in the capabilities check.
- Introduced new functions to handle quota bypass logic in club feature access and consumption.
- Updated the FeatureUsageBadge component to reflect platform exemptions for features.
- Incremented application version to 0.8.195 and database schema version to 20260606083 to reflect these changes.
- Enhanced backend routers to include new logic for consuming club features during AI-related actions.
- Incremented application version to 0.8.192 and database schema version to 20260606081.
- Updated club module versions for 'clubs' and 'club_creation_requests' to reflect recent changes.
- Implemented logic to mark approved club creation requests as 'superseded' when the associated club is deleted.
- Refactored frontend components to clear session storage for coach-related keys upon logout and during login checks.
- Enhanced onboarding page to accurately display the status of club creation requests based on their validity.
- Updated the OrgInboxContext to include handling for club creation requests, allowing for better management of inbox items.
- Refactored components to utilize the new `canShowInboxNav` and `canAccessClubCreationInbox` flags for improved access control.
- Enhanced the InboxPage to display club creation requests with appropriate actions for approval and rejection.
- Updated the DashboardOrgInboxWidget to show both club creation and join requests, improving the user interface for managing inbox items.
- Introduced endpoints for managing club creation requests, including fetching, creating, and withdrawing requests.
- Updated the onboarding page to allow users to submit new club creation requests and view their existing requests.
- Enhanced the admin interface with navigation and routing for club creation requests management.
- Incremented version to 0.8.191 to reflect these new features and updates in the application.
- Refactored the logout function in AuthContext to handle asynchronous logout operations, improving session management.
- Updated the FeatureUsageBadge component to display error messages when feature data retrieval fails, enhancing user feedback.
- Replaced lazy loading of OnboardingPage with lazyWithRetry for improved loading reliability.
- Adjusted the EntitlementsContext to determine club ID using utility functions for better governance form handling.
- 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.
- Introduced `email_verified` and `account_state` attributes in the `TenantContext` to improve user state management.
- Updated the `resolve_tenant_context` function to dynamically fetch `email_verified` status from the database and determine `account_state` based on user roles and memberships.
- Implemented `assert_min_account_state` checks across various endpoints to enforce access control based on user account status.
- Incremented version to 1.1.0 in version.py to reflect these enhancements in tenant context management and access control.
- 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.
- Updated the AI gap filling logic to include structured offers for unfilled gaps, improving the user experience in the Exercise Progression Path Builder.
- Introduced new functions for detecting off-topic steps and parsing LLM-suggested exercises, enhancing the contextual relevance of exercise suggestions.
- Enhanced the frontend components to support new AI proposal features, including quick creation modals for newly suggested exercises.
- Incremented version to 0.8.190 and updated changelog to reflect these improvements in planning AI 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.
- Introduced a new function `hybrid_ranking_ambiguous` to determine when to rerank candidates based on score proximity, improving the decision-making process for exercise suggestions.
- Updated `should_run_llm_rank_pipeline` to incorporate the new ranking logic and handle scenarios with ambiguous rankings more effectively.
- Adjusted the frontend to always include LLM ranking in requests, ensuring consistent behavior across different query lengths.
- Incremented version to 0.8.182 and updated changelog to reflect these enhancements in planning AI capabilities.
- 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 ExerciseAiQuickCreateTeaser component for a compact entry point in the exercise creation process.
- Updated ExercisePickerModal to integrate the new teaser, allowing users to expand and create exercises directly from the search results.
- Enhanced the quick create functionality with dynamic headlines and hints based on user input and context.
- Refactored conditional rendering logic to improve user experience when no exercises are found.
- Added support for the new planning exercise expectation profile slug in the AI prompt runtime.
- Refactored SQL parameter handling in the planning exercise retrieval process to ensure correct binding for full-text search.
- Updated the planning exercise suggestion logic to incorporate LLM expectation handling, improving the accuracy of exercise recommendations.
- Introduced new functions to determine when to run the LLM expectation pipeline, enhancing the decision-making process for exercise suggestions.
- Incremented version to 0.8.176 and updated changelog to reflect these enhancements in planning AI capabilities.
- Introduced new functions to generate skill profiles from exercise IDs, improving the ability to summarize skills for both units and sections.
- Updated the planning target profile to incorporate section-specific exercise IDs, allowing for more granular skill tracking and context.
- Enhanced the ExercisePickerModal and related pages to support section context, including titles, guidance notes, and exercise counts.
- Implemented expectation mode handling in the planning target pipeline to differentiate between planning references and query-only scenarios.
- Incremented version to 0.8.174 and updated changelog to reflect these enhancements in planning AI capabilities.
- Replaced the previous exercise matching logic with a new multistage planning retrieval process, improving the accuracy of exercise suggestions.
- Introduced LLM gates to limit LLM calls based on query length and intent application, optimizing performance and resource usage.
- Updated the `compose_retrieval_phase` function to include profile preselection, enhancing the retrieval process.
- Incremented version to 0.5.0 and updated changelog to reflect these significant enhancements in planning AI capabilities.
- Introduced a constant `PLANNING_SUGGEST_LIMIT` set to 50 to align with backend constraints for exercise suggestions.
- Updated the API request limit in `ExercisePickerModal` to utilize the new constant, ensuring compliance with backend specifications.
- Made `unit_id` and `group_id` optional in `PlanningExerciseSuggestRequest` to support client context without a saved unit.
- Refactored `_load_group_recent_exercise_ids` to handle cases where `exclude_unit_id` is optional.
- Introduced `build_client_planning_context_pack` for improved context handling in client-free searches.
- Updated `suggest_planning_exercises` to utilize the new client context pack when `unit_id` is not provided.
- Incremented version to 0.8.172 and updated changelog to reflect these enhancements in the planning AI capabilities.
- Introduced `planningUnitId` and `expectPlanningSearch` props to better manage planning context for exercise suggestions.
- Refactored logic to resolve planning unit ID and construct active planning context, enhancing the accuracy of exercise suggestions.
- Implemented checks to block planning search when necessary, providing clearer user feedback in the UI.
- Updated `TrainingUnitEditPage` to pass the correct planning unit ID, ensuring seamless integration with the exercise picker.
- Updated `effectivePickerQuery` logic to improve search handling based on planning context, allowing for a single input field in planning mode.
- Simplified query construction by utilizing `effectivePickerQuery` throughout the component, enhancing clarity and user experience.
- Adjusted UI elements and labels to better reflect the context of the search, providing clearer guidance for users.
- Modified `TrainingUnitEditPage` to ensure proper unit ID resolution, improving integration with the exercise picker.
- Introduced `effectivePickerQuery` to streamline search input handling, combining `debouncedSearch` and `debouncedAi` for improved query accuracy.
- Updated the `useExerciseAiQuickCreateFields` hook to use the new effective query, enhancing the quick create functionality.
- Modified conditional checks to utilize `effectivePickerQuery`, ensuring better user feedback based on search input.
- Improved placeholder text and labels for clarity in the search fields, enhancing user experience during exercise selection.
- 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.
- Introduced a new AI assistant toggle in the Exercise List Page header, allowing users to enable quick exercise creation via AI suggestions.
- Updated the ExerciseListSearchBar component to remove deprecated AI quick create functionality, streamlining the interface.
- Enhanced CSS styles for the AI assistant toggle, improving visual feedback and user interaction.
- Improved overall layout and spacing in the exercises page for better usability.
- Updated ExerciseAiQuickCreateOffer to set showSketchField to true by default and introduced sketchOptional prop for improved flexibility in exercise creation.
- Refactored ExercisePickerModal and ExercisesListPageRoot to leverage useExerciseAiQuickCreateFields hook, simplifying state management for quick create fields.
- Removed deprecated parsing logic and streamlined error handling for sketch input, enhancing user experience during exercise creation.
- Improved placeholder text and labels for clarity, ensuring better guidance for users when providing input for AI-generated exercises.
- 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.
- Updated the quick create process to include a preview feature for AI-generated exercises, allowing users to review goals, execution, preparation, and trainer notes.
- Introduced new constants for instruction fields and refactored the payload building function to utilize the preview data.
- Improved error handling to ensure at least one of the goal or execution fields is populated.
- Deprecated the previous payload building function in favor of the new preview-based approach, streamlining the exercise creation workflow.
- Updated APP_VERSION to 0.8.164 and added changelog entry for the new version.
- Enhanced ExercisePickerModal to support quick exercise creation using AI, including fields for sketch and focus area.
- Implemented error handling for AI suggestions and improved user prompts for input validation.
- Updated UI elements to reflect changes in exercise creation workflow.
- 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.
- 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.
- Added new functionality for exporting and importing matrix editor data in JSON and CSV formats within the MaturityMatrixToolsAdmin component.
- Updated the API utility functions to support matrix editor exports and imports, enhancing the backend communication for Superadmin tasks.
- Refactored the client API to streamline request handling and improve code clarity.
- Included new UI elements for file upload and download actions, improving user experience in managing matrix data.
- 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.
- 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 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.
- 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.
- Replaced hardcoded visibility labels with the new constant EXERCISE_VISIBILITY_FIELD_LABEL in multiple components, ensuring consistent terminology throughout the application.
- Updated UI text to reflect the change from "Sichtbarkeit" to "Freigabelevel" in various contexts, enhancing clarity for users.
- Improved accessibility by standardizing the visibility-related labels in the ExercisePickerModal, ExerciseProgressionGraphPanel, and other related components.
- Introduced a tabbed interface for the exercise form, allowing users to navigate between different sections (Stammdaten, Anleitung, Einordnung, etc.) more intuitively.
- Added new CSS styles for the exercise form, including improved layout and visual differentiation for various sections.
- Implemented dynamic tab management based on exercise type and edit state, enhancing user experience during form interactions.
- Refactored existing components to integrate the new tab structure, ensuring a cohesive design and functionality across the exercise form.
- Introduced snapshot and dirty check functions for variant payloads, enabling better tracking of unsaved changes.
- Implemented synchronization of saved variant snapshots to improve data integrity during edits.
- Enhanced the variant saving process with validation for variant names and automatic saving of changes.
- Updated the UI to reflect changes in variant management, ensuring a smoother user experience when editing exercise variants.
- Added a new meta panel for exercise classification and target groups, improving the organization of exercise attributes.
- Introduced ExerciseCatalogAssocEditor component to manage focus areas, training styles, and target groups, enhancing user interaction.
- Refactored CSS styles for the new meta panel and associated components, ensuring a cohesive design and improved responsiveness.
- Removed the MultiAssocBlock component to streamline the code and improve maintainability.
- Introduced a new constant, VARIANT_DIFFICULTY, to define difficulty options for exercises.
- Improved code organization by separating the import statements for better readability.
- 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 SkillTreeMultiSelect component to support dynamic positioning and improved accessibility through the use of portals.
- Refactored the dropdown panel rendering logic to enhance user experience when selecting skills.
- Added CSS styles for the exercise filter modal to improve layout and responsiveness.
- Introduced new styles for the skill tree multiselect panel, ensuring better visual integration and usability.
- Updated the FrameworkProgramsFilterBlock to include a search input and filter modal, improving user interaction and accessibility.
- Refactored CSS styles for filter components to ensure consistent layout and spacing.
- Removed deprecated panel open state management, streamlining the component logic.
- Integrated new filtering capabilities in the TrainingPlanningFrameworkImportModal and TrainingModulesListPage, enhancing the overall filtering experience.
- Improved the display of active filters and results count, providing clearer feedback to users.
- Introduced new helper functions for managing artifact type corpus, improving code organization and readability.
- Updated the `compute_club_corpus_reference` function to utilize the new corpus handling methods, enhancing clarity and maintainability.
- Refactored skill profile functions to leverage the new corpus structure, ensuring consistent data retrieval across different artifact types.
- Improved the handling of visibility clauses for library content, streamlining database queries for skill profiles.
- Enhanced the batch skill profile summary function to aggregate reference data by artifact type, improving performance and accuracy.
- Modified the `compact_profile_summary` function to allow for dynamic skill and category limits, enhancing flexibility in profile data retrieval.
- Updated frontend components to display skill weights and scores more effectively, improving user interaction with skill metrics.
- Adjusted CSS styles for skill KPI tiles to better differentiate between score and percentage displays, ensuring a clearer visual representation.
- Refactored utility functions to streamline skill summary handling, enhancing overall code maintainability and performance.
- Introduced a new function to calculate club-specific skill percentages, ensuring values are capped at 100%.
- Updated skill profile calculations to include indicators for the best club performance per skill.
- Enhanced frontend components to display club best indicators and improved layout for skill profiles.
- Refactored CSS styles for skill profile components, ensuring a more cohesive and user-friendly interface.
- Updated tests to validate new functionality and ensure accurate representation of skill metrics.
- 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.
- Introduced a new PageFormEditorChrome component for improved layout and user experience.
- Updated CSS styles for the framework editor, including danger zone and delete button hover effects.
- Refactored the TrainingFrameworkProgramEditPage to utilize the new component and streamline the action configuration.
- Enhanced the page title handling for better clarity when creating or editing framework programs.
- Updated the TrainingFrameworkProgramsListPage to utilize new CSS classes for improved layout and styling.
- Removed deprecated components and functions, streamlining the codebase for better maintainability.
- Introduced utility functions for splitting aggregated strings, enhancing data handling for framework program attributes.
- Enhanced the user interface with loading and empty state indicators, improving overall user experience.
- Introduced a new filter block for training framework programs, allowing users to refine their selections based on focus areas, training types, and target groups.
- Updated the TrainingFrameworkProgramsListPage to integrate the filter block and manage filter states effectively.
- Enhanced CSS styles for the filter block and program list, improving layout and spacing for better user experience.
- Removed unused filter-related logic from the TrainingPlanningFrameworkImportModal, streamlining the component's functionality.
- Introduced a new modal for importing training framework sessions, featuring a backdrop and panel for improved user experience.
- Added comprehensive filtering options for focus areas, training types, and target groups, utilizing a structured filter state.
- Enhanced session duration handling with distinct duration collection and display, improving clarity in program selection.
- Updated utility functions to support new filtering capabilities and session duration management, ensuring a cohesive user interface.
- 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.
- Bumped application version to 0.8.150 and updated build date and database schema version.
- Introduced new SQL migration for planned duration fields in training units and sections.
- Added functions to handle focus areas and style directions in training framework programs.
- Enhanced training planning components to support planned duration input and display.
- Updated frontend components to manage and display planned duration for training units and sections.
- Modified comments in `SkillTreePickerPanel` and `skillCatalogTree.js` to accurately reflect the default expansion behavior, specifying that only main groups are open by default.
- Refactored `defaultExpandedKeysForSkillTree` to simplify the logic, ensuring only main groups are returned as expanded.
- Adjusted tests in `skillCatalogTree.test.js` to validate the updated behavior, confirming that only main groups are opened in the skill tree.
- Simplified the rendering of skill group labels in `SkillTreePickerPanel` for improved readability.
- Updated comments in `skillCatalogTree.js` to clarify the structure of expandable nodes and default expansion behavior.
- Refactored the skill catalog tree building logic to streamline the mapping of categories and skills, enhancing performance and maintainability.
- Adjusted tests in `skillCatalogTree.test.js` to reflect changes in the structure of skill nodes, ensuring accurate validation of functionality.
- Introduced utility functions to count skills without main categories and categories, enhancing data management in the Skills Catalog Admin.
- Updated the SkillsCatalogAdmin component to handle unassigned main and category IDs, improving user experience when managing skills.
- Refactored skill selection logic to utilize new utility functions, ensuring accurate filtering of skills based on selected categories and main categories.
- Enhanced the UI to display unassigned skills clearly, improving overall usability and clarity in skill management.
- Added CSS styles for skill group labels in the skill tree to improve visual hierarchy and readability.
- Updated `SkillTreePickerPanel` and `SkillTreeMultiSelect` components to utilize the new default expansion logic, ensuring main and category nodes are open by default while skill groups remain collapsed.
- Refactored state management in `SkillTreePickerPanel` to align with the new default expansion behavior.
- Enhanced utility functions to support the new default expansion logic for skill trees.
- Introduced a `defaultCollapsed` prop in `SkillTreeMultiSelect` and `SkillTreePickerPanel` to control the initial expansion state of skill trees.
- Updated `SkillTreeSelect` to accept a `defaultCollapsed` prop, enhancing flexibility in component usage.
- Adjusted state management in `SkillTreePickerPanel` to respect the `defaultCollapsed` setting, improving user interaction with skill selection.
- Introduced new `SkillTreeSelect` and `SkillTreeMultiSelect` components for enhanced skill selection in various modals and forms.
- Updated API calls to use `listSkillsCatalog` instead of `listSkills` for improved data retrieval.
- Enhanced CSS styles for skill selection components to improve user experience and visual consistency across the application.
- 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.
- Introduced new CSS styles for exercise cards and selection sections, improving visual feedback for selected exercises.
- Updated ExerciseListCard to support a new `selectionPinned` prop, allowing for a badge display on selected exercises.
- Refactored selection handling in ExercisesListPageRoot to manage selected entries more effectively, replacing the previous Set-based approach.
- Enhanced SaveSelectedExercisesAsModuleModal to support appending exercises to existing modules, improving module management capabilities.
- Updated session state handling to include selected entries, ensuring persistence across sessions.
- Added clickable behavior to exercise card body, allowing users to navigate to exercise details by clicking anywhere on the card.
- Introduced keyboard accessibility for exercise cards, enabling navigation via Enter and Space keys.
- Updated ExerciseListBulkToolbar to include a new button for saving selected exercises as a module, enhancing bulk action capabilities.
- Improved CSS styles for clickable exercise card body to indicate interactivity.
- Added a new `handleSaveAndClose` function to allow users to save and navigate back to the exercise list.
- Updated `performSaveAttempt` to accept a `closeAfter` parameter for conditional navigation.
- Refactored form submission handling to include separate actions for saving and saving with closure.
- Integrated `PageFormEditorChrome` for improved layout and user experience, including a back navigation option.
- Updated the `list_exercises` function to include counts for exercise variants and media, improving data retrieval for exercise details.
- Added new CSS styles for the exercise card footer to display variant and media statistics in a visually appealing manner.
- Implemented `ExerciseCardContentStats` component to conditionally render variant and media counts, enhancing the user interface of exercise cards.
- Updated PlanningLayout to conditionally render the PlanningRouteNav based on the current path, improving navigation for planning unit editors.
- Enhanced TrainingUnitEditPage with unsaved changes detection, integrating a prompt for users to confirm before leaving the page with unsaved changes.
- Introduced utility functions for creating a stable snapshot of form data to facilitate dirty-checking, ensuring better user experience during form editing.
- Added tests for the new utility functions to validate their behavior in various scenarios.
- Updated CSS styles for the full-page editor, modifying the header to include a back link and title, while fixing the action dock for all viewports.
- Removed the sticky header and integrated the action bar at the bottom for improved usability across devices.
- Simplified the PageFormEditorChrome component by eliminating unnecessary memoization and restructuring the header layout.
