VERA documentation

VERA packages a source document, parsed structure, embeddings, keyword index, figures, and citation metadata in one portable .vera file.

Start here

• Getting started — install VERA, convert a PDF, and run the first cited search.
• Run the desktop app — install dependencies, start the development app, and create an unpacked build.
• Examples and recipes — copyable workflows for individual documents and document libraries.
• Troubleshooting — installation, conversion, search, indexing, and optional-dependency problems.

User guides

• Convert documents
• Search documents
• Search and index document libraries
• Work with figures and highlight regions
• Validate archives and export source documents
• Evaluate retrieval quality
• Use the Python API
• Connect an MCP client

Reference

• CLI reference — command overview with links to the exhaustive JSON and exit-code contract.
• API reference — generated Python API docs.
• Current VERA 0.2 format specification
• Legacy VERA 0.1 format specification
• Collection index design and behavior
• Library index structure diagrams
• Portable Agent Skill
• Agent-skill installation and authoring

Contributor and architecture documentation

• Repository architecture
• Desktop app architecture
• Development handoff

The README is the product overview, these pages are the human user documentation, and skills/vera/ is the self-contained package for AI agents. When behavior changes, update all affected layers in the same change.