Darwin Mobile Agent Model Card
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Darwin Mobile Agent Model Card
| Field | Value |
|---|---|
| Repository | ai-agents-2030/darwin-mobile-agent |
| Category | Mobile Agent Self-Evolution Framework |
| Stars / forks snapshot | 10 / 0 |
| Language | Python |
| License | Apache-2.0 |
| Raw capture | raw-github/ai-agents-2030_darwin-mobile-agent.md |
| Updated by | hourly public metadata update, 2026-05-29 16:12 +0800 |
1. Role in Self Evolve
darwin-mobile-agent targets self-evolving mobile automation agents with an explicit iterative improvement workflow. It matters because self-evolving agents need repeatable harness control, measurable feedback loops, and reusable skill procedures before claiming stable improvement.
2. Working Principle
run mobile task execution loops -> record failures and intervention traces -> evolve prompts/skills/action plans -> replay against app tasks to measure iterative gains
3. Evidence Path
web-observed GitHub page showed 10 stars, 0 forks, 4 commits, Apache-2.0 license, and README references to a self-evolving mobile-agent architecture. Shell GitHub API access remained blocked by DNS and local gh auth was invalid, so this card treats the snapshot as web-observed rather than API-verified.
4. Teaching Use
Use this card to explain Mobile Agent Self-Evolution Framework: it shows how harness/runtime/benchmark layers convert agent behavior into reproducible and auditable engineering workflows.
5. Limits
The repository was not cloned in this iteration; no benchmark run, plugin install, workflow execution, or agent loop experiment was executed. Counts and claims are visible public-page/search signals unless independently revalidated later.