Files
wifi-densepose/.claude/commands/hooks/pre-task.md
Claude 6ed69a3d48 feat: Complete Rust port of WiFi-DensePose with modular crates
Major changes:
- Organized Python v1 implementation into v1/ subdirectory
- Created Rust workspace with 9 modular crates:
  - wifi-densepose-core: Core types, traits, errors
  - wifi-densepose-signal: CSI processing, phase sanitization, FFT
  - wifi-densepose-nn: Neural network inference (ONNX/Candle/tch)
  - wifi-densepose-api: Axum-based REST/WebSocket API
  - wifi-densepose-db: SQLx database layer
  - wifi-densepose-config: Configuration management
  - wifi-densepose-hardware: Hardware abstraction
  - wifi-densepose-wasm: WebAssembly bindings
  - wifi-densepose-cli: Command-line interface

Documentation:
- ADR-001: Workspace structure
- ADR-002: Signal processing library selection
- ADR-003: Neural network inference strategy
- DDD domain model with bounded contexts

Testing:
- 69 tests passing across all crates
- Signal processing: 45 tests
- Neural networks: 21 tests
- Core: 3 doc tests

Performance targets:
- 10x faster CSI processing (~0.5ms vs ~5ms)
- 5x lower memory usage (~100MB vs ~500MB)
- WASM support for browser deployment
2026-01-13 03:11:16 +00:00

2.1 KiB

hook pre-task

Execute pre-task preparations and context loading.

Usage

npx claude-flow hook pre-task [options]

Options

  • --description, -d <text> - Task description for context
  • --auto-spawn-agents - Automatically spawn required agents (default: true)
  • --load-memory - Load relevant memory from previous sessions
  • --optimize-topology - Select optimal swarm topology
  • --estimate-complexity - Analyze task complexity

Examples

Basic pre-task hook

npx claude-flow hook pre-task --description "Implement user authentication"

With memory loading

npx claude-flow hook pre-task -d "Continue API development" --load-memory

Manual agent control

npx claude-flow hook pre-task -d "Debug issue #123" --auto-spawn-agents false

Full optimization

npx claude-flow hook pre-task -d "Refactor codebase" --optimize-topology --estimate-complexity

Features

Auto Agent Assignment

  • Analyzes task requirements
  • Determines needed agent types
  • Spawns agents automatically
  • Configures agent parameters

Memory Loading

  • Retrieves relevant past decisions
  • Loads previous task contexts
  • Restores agent configurations
  • Maintains continuity

Topology Optimization

  • Analyzes task structure
  • Selects best swarm topology
  • Configures communication patterns
  • Optimizes for performance

Complexity Estimation

  • Evaluates task difficulty
  • Estimates time requirements
  • Suggests agent count
  • Identifies dependencies

Integration

This hook is automatically called by Claude Code when:

  • Starting a new task
  • Resuming work after a break
  • Switching between projects
  • Beginning complex operations

Manual usage in agents:

# In agent coordination
npx claude-flow hook pre-task --description "Your task here"

Output

Returns JSON with:

{
  "continue": true,
  "topology": "hierarchical",
  "agentsSpawned": 5,
  "complexity": "medium",
  "estimatedMinutes": 30,
  "memoryLoaded": true
}

See Also

  • hook post-task - Post-task cleanup
  • agent spawn - Manual agent creation
  • memory usage - Memory management
  • swarm init - Swarm initialization