artemis vs GenericAgent
The two are close in size: 13.1k stars for artemis, 14.3k for GenericAgent. Over the days we have tracked them artemis moved +975.3% and GenericAgent +5.8%, so artemis is growing faster right now.
They split the axes: artemis leads on noise control and customization, GenericAgent on context depth and model freedom.
Stars and commit dates come from our own daily tracking. The six axes are read off each project's documentation by our review pipeline, so they describe what a project says about itself, not what we measured in its code.
Where they stand today
Provides a native MCP server that lets AI IDE assistants drive real Android devices with multimodal targeting, safety nets, and replayable diagnostics.
- Stars
- 13.1k
- Tracked growth
- +975.3%
- Maturity
- ●●●●●
- Last commit
- 18d ago
- Language
- Python
- License
- Apache-2.0
- Cost to run
- Self-hosted runtime; model usage may incur cloud API costs
Self-evolving agent that crystallizes each solved task into a persistent, reusable personal skill tree from a minimal (~3K-line) seed.
- Stars
- 14.3k
- Tracked growth
- +5.8%
- Maturity
- ●●●●●
- Last commit
- 1d ago
- Language
- Python
- License
- MIT
- Cost to run
- Your LLM API key; provider charges apply
Six axes, head to head
Each axis runs 0 to 5. The label under a score is what that project's own docs claim, not a category average.
| Axis | artemis | GenericAgent |
|---|---|---|
Context depth How much of your codebase it sees before it answers: the open diff, the diff plus related files, or the whole repository. | ●●●●● Diff + related files | ●●●●● Whole-repo analysis |
Noise control How it keeps output volume down — severity thresholds, deduplication, incremental runs over new commits only. | ●●●●● Pre-exec Safety Net | ●●●●● Human-in-the-loop |
Customization How far it bends to your team: custom rules, prompts, style guides, per-path config. | ●●●●● Custom rules & profiles | ●●●●● Config & prompts |
Privacy Whether your code stays on your own infrastructure: fully local, self-hostable, or cloud API only. | ●●●●● Self-hostable | ●●●●● Cloud API key |
Model freedom Whether you can point it at any provider, or it is wired to one. | ●●●●● Multiple providers | ●●●●● Bring-your-own-key |
Setup ease What it takes to get a first useful run out of it. | ●●●●● One-click start | ●●●●● One-line installer |
Which one to pick
Pick artemis if…
Easy setup — one-click local server and native MCP IDE integrations to run reliable, safety-gated automation on real Android devices with rich diagnostics.
- Noise control: Pre-exec Safety Net (5/5 against 3/5)
- Customization: Custom rules & profiles (5/5 against 3/5)
Pick GenericAgent if…
Self-evolving — pick this when you want an agent that autonomously builds reusable skills and gains system-level desktop/browser control over time.
- Context depth: Whole-repo analysis (5/5 against 3/5)
- Model freedom: Bring-your-own-key (5/5 against 3/5)
What people want from each one
google/artemis
lsdefine/GenericAgent
Questions people ask
Is artemis better than GenericAgent?
They split the axes: artemis leads on noise control and customization, GenericAgent on context depth and model freedom. artemis is worth picking when easy setup — one-click local server and native MCP IDE integrations to run reliable, safety-gated automation on real Android devices with rich diagnostics.
Which of artemis and GenericAgent keeps my code private?
artemis: Self-hostable (4/5). GenericAgent: Cloud API key (3/5).
What does each one cost to run?
artemis: Self-hosted runtime; model usage may incur cloud API costs. GenericAgent: Your LLM API key; provider charges apply.
Full profiles: google/artemis and lsdefine/GenericAgent. Everything else in Computer use.