schema: spec-driven

# Project context (optional)
# This is shown to AI when creating artifacts.
# Add your tech stack, conventions, style guides, domain knowledge, etc.
context: |
  Tech stack: Python 3.10+, PyTorch, DINOv2, SAM 2.1, LanceDB, Typer, Dash, Plotly
  Dependencies: transformers, torch, torchvision, lancedb, polars, dash, typer, pydantic
  Build tools: UV (package manager), pytest (testing), justfile (tasks), jujutsu (Version Control)

  Conventions:
  - Google Python Style Guide
  - TDD: Write tests before implementation
  - Single-layer nesting max in conditionals/loops
  - English comments only

  Domain: Vision-language navigation and image feature retrieval
  - Feature extraction using DINOv2 (facebook/dinov2-large)
  - Image segmentation using SAM 2.1 (facebook/sam2.1-hiera-large)
  - Vector storage and retrieval with LanceDB
  - Feature compression for efficient storage

# Per-artifact rules (optional)
# Add custom rules for specific artifacts.
rules:
  proposal:
    - Keep proposals under 500 words
    - Always include a "Non-goals" section
    - Focus on incremental changes
  tasks:
    - Break tasks into chunks of max 2 hours
    - Write tests before implementation code