AI-powered mobile automation agent — describe what you want in plain English, AppClaw reads the screen, reasons, and acts. LLM-agnostic, open-source, zero telemetry.
- capability exposureinferred+35
- trust mitigatorsmixed−3
inferredmixed
The A–E grade is our heuristic synthesis — a "review this" prompt, not a verdict. Each factor is tagged by what backs it: attested (a verifiable record), reported (a third party's claim), or inferred (our own heuristic, e.g. permissions). See methodology.
graded 1m ago · see ecosystem CVEs →
- A · 0 → B · 32
No known CVEs for this server.
No tool-safety findings — heuristic detectors run on the compute-risk cadence; a finding appears when a tool trips a rule.
analyzed commit be5f03d · analyzer v20 · 4h ago
skills & prompt files 6
- skillAppiumTestDistribution-AppClaw-be5f03d/.agents/skills/emil-design-eng/SKILL.md
- skillAppiumTestDistribution-AppClaw-be5f03d/.agents/skills/generate-appclaw-flow/SKILL.md
- skillAppiumTestDistribution-AppClaw-be5f03d/.agents/skills/review-changes/SKILL.md
- skillAppiumTestDistribution-AppClaw-be5f03d/.agents/skills/use-appclaw-agent-cli/SKILL.md
- skillAppiumTestDistribution-AppClaw-be5f03d/.agents/skills/use-appclaw-cli/SKILL.md
- agent-rulesAppiumTestDistribution-AppClaw-be5f03d/CLAUDE.md
[](https://mcpobservatory.com/servers/github:AppiumTestDistribution/AppClaw/security) Heuristic, inferred signals — false positives (legitimately powerful tools, forks, language ports) are expected. Treat each as "review this", not a verdict. See the ecosystem-wide picture on the security hub, or the fleet security of AppiumTestDistribution.