e-filing/AGENTS.md

AGENTS.md

Project Context

Goal: Automate the e-filing process for legal documents.

Approach: Research-driven development. We first study how filing works today — both the manual process and competitor solutions — before building an automated solution.

Directory Structure

Path	Purpose
videos/	Reference videos: manual filing walkthroughs + competitor demos
docs/research/	Research notes, video transcripts, skill-based analyses
app/	Production codebase (Python, managed with uv)

Key Guidelines for AI Agents

Phase 1 — Research

• Analyze videos in videos/ to understand the manual e-filing flow
• Compare with competitor automated solutions
• Document findings as structured notes in docs/research/
• Skills may be used to extract insights, frame captures, or transcripts from the video content
• Each research artifact should be self-contained and reference its source video

Phase 2 — Build

• All implementation lives in app/
• Use Python as the language
• Use uv for dependency management (pyproject.toml, not requirements.txt)
• Virtual environments are managed by uv (no manual venv)
• Keep research docs separate from code — docs/research/ is for knowledge, app/ is for implementation

Coding Standards

• Prefer clarity and readability over cleverness
• Reference the research when designing features
• Document assumptions and decisions in the code or as docstrings
• Use structured output formats (JSON, markdown) where applicable