5e9bc28abe
This commit significantly improves the functionality by implementing fuzzy semantic search to find contextually relevant dependencies: - Add Fuse.js for powerful fuzzy search capability with weighted multi-field matching - Implement score-based relevance ranking with high/medium relevance tiers - Enhance context generation to include detailed information about similar tasks - Fix context shadowing issue that prevented detailed task information from reaching the AI model - Add informative CLI output showing semantic search results and dependency patterns - Improve formatting of dependency information in prompts with task titles The result is that newly created tasks are automatically placed within the correct dependency structure without manual intervention, with the AI having much better context about which tasks are most relevant to the new one being created. This significantly improves the user experience by reducing the need to manually update task dependencies after creation, all without increasing token usage or costs.
68 lines
3.3 KiB
Plaintext
68 lines
3.3 KiB
Plaintext
# Task ID: 90
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# Title: Implement Subtask Progress Analyzer and Reporting System
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# Status: pending
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# Dependencies: 1, 3
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# Priority: medium
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# Description: Develop a subtask analyzer that monitors the progress of all subtasks, validates their status, and generates comprehensive reports for users to track project advancement.
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# Details:
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The subtask analyzer should be implemented with the following components and considerations:
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1. Progress Tracking Mechanism:
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- Create a function to scan the task data structure and identify all tasks with subtasks
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- Implement logic to determine the completion status of each subtask
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- Calculate overall progress percentages for tasks with multiple subtasks
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2. Status Validation:
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- Develop validation rules to check if subtasks are progressing according to expected timelines
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- Implement detection for stalled or blocked subtasks
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- Create alerts for subtasks that are behind schedule or have dependency issues
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3. Reporting System:
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- Design a structured report format that clearly presents:
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- Overall project progress
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- Task-by-task breakdown with subtask status
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- Highlighted issues or blockers
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- Support multiple output formats (console, JSON, exportable text)
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- Include visual indicators for progress (e.g., progress bars in CLI)
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4. Integration Points:
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- Hook into the existing task management system
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- Ensure the analyzer can be triggered via CLI commands
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- Make the reporting feature accessible through the main command interface
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5. Performance Considerations:
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- Optimize for large task lists with many subtasks
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- Implement caching if necessary to avoid redundant calculations
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- Ensure reports generate quickly even for complex project structures
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The implementation should follow the existing code style and patterns, leveraging the task data structure already in place. The analyzer should be non-intrusive to existing functionality while providing valuable insights to users.
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# Test Strategy:
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Testing for the subtask analyzer should include:
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1. Unit Tests:
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- Test the progress calculation logic with various task/subtask configurations
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- Verify status validation correctly identifies issues in different scenarios
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- Ensure report generation produces consistent and accurate output
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- Test edge cases (empty subtasks, all complete, all incomplete, mixed states)
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2. Integration Tests:
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- Verify the analyzer correctly integrates with the existing task data structure
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- Test CLI command integration and parameter handling
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- Ensure reports reflect actual changes to task/subtask status
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3. Performance Tests:
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- Benchmark report generation with large task sets (100+ tasks with multiple subtasks)
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- Verify memory usage remains reasonable during analysis
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4. User Acceptance Testing:
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- Create sample projects with various subtask configurations
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- Generate reports and verify they provide clear, actionable information
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- Confirm visual indicators accurately represent progress
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5. Regression Testing:
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- Verify that the analyzer doesn't interfere with existing task management functionality
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- Ensure backward compatibility with existing task data structures
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Documentation should be updated to include examples of how to use the new analyzer and interpret the reports. Success criteria include accurate progress tracking, clear reporting, and performance that scales with project size.
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