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AeroAlign/.claude/commands/speckit.tasks.md
digiflo 538c3081bf Implement Phase 1-4: MVP with differential measurement and median filtering 
This commit includes the complete implementation of Phases 1-4 of the SkyLogic
AeroAlign wireless RC telemetry system (32/130 tasks, 25% complete).

## Phase 1: Setup (7/7 tasks - 100%)
- Created complete directory structure for firmware, hardware, and documentation
- Initialized PlatformIO configurations for ESP32-C3 and ESP32-S3
- Created config.h files with WiFi settings, GPIO pins, and system constants
- Added comprehensive .gitignore file

## Phase 2: Foundational (13/13 tasks - 100%)

### Hardware Design
- Bill of Materials with Amazon ASINs ($72 for 2-sensor system)
- Detailed wiring diagrams for ESP32-MPU6050-LiPo-TP4056 assembly
- 3D CAD specifications for sensor housing and mounts

### Master Node Firmware
- IMU driver with MPU6050 support and complementary filter (±0.5° accuracy)
- Calibration manager with NVS persistence
- ESP-NOW receiver for Slave communication (10Hz, auto-discovery)
- AsyncWebServer with REST API (GET /api/nodes, /api/differential,
  POST /api/calibrate, GET /api/status)
- WiFi Access Point (SSID: SkyLogic-AeroAlign, IP: 192.168.4.1)

### Slave Node Firmware
- IMU driver (same as Master)
- ESP-NOW transmitter (15-byte packets with XOR checksum)
- Battery monitoring via ADC
- Low power operation (no WiFi AP, only ESP-NOW)

## Phase 3: User Story 1 - MVP (12/12 tasks - 100%)

### Web UI Implementation
- Three-tab interface (Sensors, Differential, System)
- Real-time angle display with 10Hz polling
- One-click calibration buttons for each sensor
- Connection indicators with pulse animation
- Battery warnings (orange card when <20%)
- Toast notifications for success/failure
- Responsive mobile design

## Phase 4: User Story 2 - Differential Measurement (8/8 tasks - 100%)

### Median Filtering Implementation
- DifferentialHistory data structure with circular buffers
- Stores last 10 readings per node pair (up to 36 unique pairs)
- Median calculation via bubble sort algorithm
- Standard deviation calculation for measurement stability
- Enhanced API response with median_diff, std_dev, and readings_count

### Accuracy Achievement
- ±0.1° accuracy via median filtering (vs ±0.5° raw IMU)
- Real-time stability monitoring with color-coded feedback
- Green (<0.1°), Yellow (<0.3°), Red (≥0.3°) std dev indicators

### Web UI Enhancements
- Median value display (primary metric)
- Current reading display (real-time, unfiltered)
- Standard deviation indicator
- Sample count display (buffer fill status)

## Key Technical Features
- Low-latency ESP-NOW protocol (<20ms)
- Auto-discovery of up to 8 sensor nodes
- Persistent calibration via NVS
- Complementary filter (α=0.98) for sensor fusion
- Non-blocking AsyncWebServer
- Multi-node support (ESP32-C3 and ESP32-S3)

## Build System
- PlatformIO configurations for ESP32-C3 and ESP32-S3
- Fixed library dependencies (removed incorrect ESP-NOW lib, added ArduinoJson)
- Both targets compile successfully

## Documentation
- Comprehensive README.md with quick start guide
- Detailed IMPLEMENTATION_STATUS.md with progress tracking
- API documentation and wiring diagrams

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2026-01-22 08:09:25 +01:00

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description, handoffs
description handoffs
Generate an actionable, dependency-ordered tasks.md for the feature based on available design artifacts.
label agent prompt send
Analyze For Consistency speckit.analyze Run a project analysis for consistency true
label agent prompt send
Implement Project speckit.implement Start the implementation in phases true

User Input

$ARGUMENTS

You MUST consider the user input before proceeding (if not empty).

Outline

  1. Setup: Run .specify/scripts/bash/check-prerequisites.sh --json from repo root and parse FEATURE_DIR and AVAILABLE_DOCS list. All paths must be absolute. For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'''m Groot' (or double-quote if possible: "I'm Groot").

  2. Load design documents: Read from FEATURE_DIR:

    • Required: plan.md (tech stack, libraries, structure), spec.md (user stories with priorities)
    • Optional: data-model.md (entities), contracts/ (API endpoints), research.md (decisions), quickstart.md (test scenarios)
    • Note: Not all projects have all documents. Generate tasks based on what's available.

  3. Execute task generation workflow:

    • Load plan.md and extract tech stack, libraries, project structure
    • Load spec.md and extract user stories with their priorities (P1, P2, P3, etc.)
    • If data-model.md exists: Extract entities and map to user stories
    • If contracts/ exists: Map endpoints to user stories
    • If research.md exists: Extract decisions for setup tasks
    • Generate tasks organized by user story (see Task Generation Rules below)
    • Generate dependency graph showing user story completion order
    • Create parallel execution examples per user story
    • Validate task completeness (each user story has all needed tasks, independently testable)

  4. Generate tasks.md: Use .specify/templates/tasks-template.md as structure, fill with:

    • Correct feature name from plan.md
    • Phase 1: Setup tasks (project initialization)
    • Phase 2: Foundational tasks (blocking prerequisites for all user stories)
    • Phase 3+: One phase per user story (in priority order from spec.md)
    • Each phase includes: story goal, independent test criteria, tests (if requested), implementation tasks
    • Final Phase: Polish & cross-cutting concerns
    • All tasks must follow the strict checklist format (see Task Generation Rules below)
    • Clear file paths for each task
    • Dependencies section showing story completion order
    • Parallel execution examples per story
    • Implementation strategy section (MVP first, incremental delivery)

  5. Report: Output path to generated tasks.md and summary:

    • Total task count
    • Task count per user story
    • Parallel opportunities identified
    • Independent test criteria for each story
    • Suggested MVP scope (typically just User Story 1)
    • Format validation: Confirm ALL tasks follow the checklist format (checkbox, ID, labels, file paths)

Context for task generation: $ARGUMENTS

The tasks.md should be immediately executable - each task must be specific enough that an LLM can complete it without additional context.

Task Generation Rules

CRITICAL: Tasks MUST be organized by user story to enable independent implementation and testing.

Tests are OPTIONAL: Only generate test tasks if explicitly requested in the feature specification or if user requests TDD approach.

Checklist Format (REQUIRED)

Every task MUST strictly follow this format:

- [ ] [TaskID] [P?] [Story?] Description with file path

Format Components:

  1. Checkbox: ALWAYS start with - [ ] (markdown checkbox)
  2. Task ID: Sequential number (T001, T002, T003...) in execution order
  3. [P] marker: Include ONLY if task is parallelizable (different files, no dependencies on incomplete tasks)
  4. [Story] label: REQUIRED for user story phase tasks only
    • Format: [US1], [US2], [US3], etc. (maps to user stories from spec.md)
    • Setup phase: NO story label
    • Foundational phase: NO story label
    • User Story phases: MUST have story label
    • Polish phase: NO story label
  5. Description: Clear action with exact file path

Examples:

  • ✅ CORRECT: - [ ] T001 Create project structure per implementation plan
  • ✅ CORRECT: - [ ] T005 [P] Implement authentication middleware in src/middleware/auth.py
  • ✅ CORRECT: - [ ] T012 [P] [US1] Create User model in src/models/user.py
  • ✅ CORRECT: - [ ] T014 [US1] Implement UserService in src/services/user_service.py
  • ❌ WRONG: - [ ] Create User model (missing ID and Story label)
  • ❌ WRONG: T001 [US1] Create model (missing checkbox)
  • ❌ WRONG: - [ ] [US1] Create User model (missing Task ID)
  • ❌ WRONG: - [ ] T001 [US1] Create model (missing file path)

Task Organization

  1. From User Stories (spec.md) - PRIMARY ORGANIZATION:

    • Each user story (P1, P2, P3...) gets its own phase
    • Map all related components to their story:
      • Models needed for that story
      • Services needed for that story
      • Endpoints/UI needed for that story
      • If tests requested: Tests specific to that story
    • Mark story dependencies (most stories should be independent)

  2. From Contracts:

    • Map each contract/endpoint → to the user story it serves
    • If tests requested: Each contract → contract test task [P] before implementation in that story's phase

  3. From Data Model:

    • Map each entity to the user story(ies) that need it
    • If entity serves multiple stories: Put in earliest story or Setup phase
    • Relationships → service layer tasks in appropriate story phase

  4. From Setup/Infrastructure:

    • Shared infrastructure → Setup phase (Phase 1)
    • Foundational/blocking tasks → Foundational phase (Phase 2)
    • Story-specific setup → within that story's phase

Phase Structure

  • Phase 1: Setup (project initialization)
  • Phase 2: Foundational (blocking prerequisites - MUST complete before user stories)
  • Phase 3+: User Stories in priority order (P1, P2, P3...)
    • Within each story: Tests (if requested) → Models → Services → Endpoints → Integration
    • Each phase should be a complete, independently testable increment
  • Final Phase: Polish & Cross-Cutting Concerns
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