Personal Atlas

Managing personal data across scattered chats and notes often leads to loss of context and fragmented memories. Personal Atlas organizes your data into a traceable, version-controlled repository using Git. It builds a structured library where every fact is backed by a source, linked via a JSON relationship graph, and accessible through semantic Markdown files.

What it does

• Structured ingestion captures raw input, dialogue, or documents while preserving original sources and timestamps.
• Graph-based navigation uses a JSON-linked directory to map relationships between entities and thematic domains.
• Version-controlled storage saves all data to a user-provided Git repository (GitHub, GitLab, Gitee) for full ownership.
• Interactive visualization generates HTML maps and relationship diagrams to browse the entire knowledge base.
• Automated interviewing guides users through twelve thematic dimensions to fill information gaps and refine profiles.

How it works

1. Connect a Git repository via existing environment tools or MCP connectors to establish the atlas/ storage root.
2. Onboard through a guided interview process or by importing existing Markdown and JSON records.
3. Query the atlas using keyword search, relationship hopping, or chronological timeline filters.
4. Update information by submitting atomic commits that synchronize records, sources, and graph metadata simultaneously.

Frameworks & tools

The skill requires a Python environment for graph validation and HTML generation. It relies on standard Git protocols and integrates with GitHub, GitLab, or Gitee via existing agent capabilities or plugins.

Why this beats prompting it yourself

Manual prompting lacks a persistent, structured memory, often resulting in hallucinations or forgotten details. This skill enforces strict schema validation and Git-backed traceability, ensuring personal facts remain consistent and auditable over time.

Use cases

• Build a persistent "digital twin" or personal knowledge base that outlives a single chat session.
• Document complex life events or career milestones with specific evidence and linked relationships.
• Organize fragmented research notes into a navigable graph with clear source attribution.

Known limitations

Requires an external Git repository and environment-level authorization to function. Python is necessary for structural validation and HTML visualization features.