38 lines
1.5 KiB
Markdown
38 lines
1.5 KiB
Markdown
# AGENTS.md
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## Project Context
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**Goal**: Automate the e-filing process for legal documents.
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**Approach**: Research-driven development. We first study how filing works today — both the manual process and competitor solutions — before building an automated solution.
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## Directory Structure
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| Path | Purpose |
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|------|---------|
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| `videos/` | Reference videos: manual filing walkthroughs + competitor demos |
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| `docs/research/` | Research notes, video transcripts, skill-based analyses |
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| `app/` | Production codebase (Python, managed with uv) |
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## Key Guidelines for AI Agents
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### Phase 1 — Research
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- Analyze videos in `videos/` to understand the manual e-filing flow
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- Compare with competitor automated solutions
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- Document findings as structured notes in `docs/research/`
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- Skills may be used to extract insights, frame captures, or transcripts from the video content
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- Each research artifact should be self-contained and reference its source video
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### Phase 2 — Build
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- All implementation lives in `app/`
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- Use **Python** as the language
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- Use **uv** for dependency management (`pyproject.toml`, not `requirements.txt`)
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- Virtual environments are managed by uv (no manual `venv`)
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- Keep research docs separate from code — `docs/research/` is for knowledge, `app/` is for implementation
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### Coding Standards
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- Prefer clarity and readability over cleverness
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- Reference the research when designing features
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- Document assumptions and decisions in the code or as docstrings
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- Use structured output formats (JSON, markdown) where applicable
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