AIContext

skill
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  • License — License: MIT
  • Description — Repository has a description
  • Active repo — Last push 0 days ago
  • Low visibility — Only 9 GitHub stars
Code Pass
  • Code scan — Scanned 12 files during light audit, no dangerous patterns found
Permissions Pass
  • Permissions — No dangerous permissions requested
Purpose
This tool ingests and normalizes personal data from your local machine—such as browser history, coding sessions, and AI chat logs—into a local SQLite database. It uses this data to generate a context profile that helps AI assistants better understand your workflow and habits.

Security Assessment
The tool inherently accesses highly sensitive data, including web browser history and local AI session logs. However, the code scan verified that it makes no network requests, contains no hardcoded secrets, and does not request dangerous execution permissions. It restricts its changes to a local folder and a local database, meaning your data is not uploaded or synced to the cloud. It also asks for user consent before scanning specific data sources. Overall risk is rated as Medium because of the highly sensitive nature of the local data it parses, despite its strong local-first privacy design.

Quality Assessment
The project is very new and has low community visibility with only 9 GitHub stars, meaning it has not yet been widely battle-tested. On a positive note, it is actively maintained, includes a CI pipeline, is distributed via PyPI, and uses a permissive MIT license.

Verdict
Use with caution: the code itself appears safe and local-only, but the tool deeply accesses highly sensitive personal data, making it suitable only for users who fully understand and accept the risks of aggregating this information.
SUMMARY

Your agents should already know you.

README.md

AIContext

CI
PyPI
Discord community

The personal context layer for AI agents.

Local-first, private by default, and built to help agents start from your real context — not a blank slate.

aicontext gives agents access to relevant personal context from your own data: coding sessions, browser history, AI conversations, and exported archives. Instead of asking you to repeatedly reconstruct what you were doing, the agent can recover the surrounding thread itself. Recent activity and long-term history combine across sources to surface not just what you did, but who you are: your skills, your curiosities, your habits, and where your attention is going next.

This is not just memory for chatbots.
It is a system for ingesting, normalizing, and querying the artifacts of your digital life so agents can better understand what a task is connected to: what you worked on, what you looked at, what you already tried, and what may matter now.

Everything stays under your control. Data is ingested locally, stored locally, and queried locally. No cloud sync, no uploads, no external storage.

Install

pip install sophonme-aicontext && aicontext install

Or, from source:

git clone https://github.com/SophonMe/AIContext.git
cd AIContext
pip install -e . && aicontext install

aicontext install scans your machine for supported local data sources, asks for consent before including each source type, ingests approved data into a local SQLite database, and installs the local agent configuration used by supported tools such as Claude Code, Codex, Pi, and OpenClaw.

It does not upload your data or require any cloud service. Changes are limited to local configuration and the ~/.aicontext/ directory, and everything can be removed later with aicontext uninstall.

Scanning for local data sources...

  [found] Claude Code sessions
          /Users/you/.claude/projects
         Include? [Y/n] y
          -> included

  [found] Chrome browser history
          /Users/you/Library/Application Support/Google/Chrome/Default/History
         Include? [Y/n] y
          -> included

Ingesting data...

  Source              Parsed    New  Updated
  ──────────────────────────────────────────
  Claude Code         12,847  12,847        0
  Chrome               8,456   8,456        0
  ──────────────────────────────────────────
  Total               21,303  21,303        0

  Generated SKILL.md  -> ~/.aicontext/skill/SKILL.md
  Claude Code agent   -> ~/.claude/agents/sophonme-context-engine.md
  Codex agent         -> ~/.codex/agents/sophonme-context-engine.toml
  Pi / OpenClaw skill -> ~/.agents/skills/personal-data
  Background sync     -> hourly via launchd (sophonme.aicontext)

Done. The sophonme-context-engine agent is now active in Claude Code, Codex, Pi, and OpenClaw.

Example Prompts

How it works

After install, Claude Code and Codex both have a sophonme-context-engine agent. The agent queries your local activity database to surface relevant context for whatever task you're working on.

A background periodic local ingest service (launchd on macOS) re-ingests your data every hour, so context stays fresh without any manual steps.

~/.aicontext/
 ├── data/
 │   ├── activity.db       — unified timeline
 │   └── reference_data/   — full session content
 └── skill/
     ├── SKILL.md
     ├── reference/        — per-source schema docs
     └── scripts/
         └── query.py      — read-only SQL query tool

The agent reads from ~/.aicontext/ using a read-only SQL query script. It never writes to your data, and never sends anything outside your machine.

Supported sources

Source Data
Claude Code Session history, prompts, project paths
Codex Session history, prompts
Chrome Browser visits, downloads
Edge Browser visits, downloads
Dia Browser visits, downloads
Safari Browser visits

More sources coming soon.

Supported agents

Agent Type
Claude Code Subagent
Codex Subagent
Pi Skill
OpenClaw Skill

Troubleshooting

If you use Codex, older app versions may need this in ~/.codex/config.toml for spawned-subagent support:

[features]
multi_agent = true

If your Codex build already supports spawned agents by default, you do not need this. Restart Codex after changing the config.

Privacy

All data is stored locally at ~/.aicontext/. Nothing is sent to any server. The agent only reads from this directory.

However, when an agent queries your data, the results become part of the prompt sent to the model provider (Anthropic, OpenAI, etc.). This means fragments of your personal history may reach the provider's API. Choose a provider you trust, and consider disabling model training on your data to avoid your personal context being used to improve future models:

Contributing

Contributions are welcome, especially new data sources.

The easiest way to contribute is to add a new source under aicontext/sources/. Each source is a single file that implements two methods: ingest_activity() for timeline records and ingest_reference() for full session content. See sources/claude_code.py for the smallest complete example.

Good source ideas include Firefox, Arc, Obsidian, Zotero, Spotify, and shell history.

If you want feedback before building, open an issue with the source you have in mind and any notes on the schema or data shape. That makes it easier to align on fit before you start.

If this project is useful to you, consider giving it a star — it helps more people find it.

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