optics-framework: Open-source test automation for Android, iOS, web, smart TV and Bluetooth devices

by mozarkai · MCP Server · ★ 65

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install optics-framework

pip install "optics-framework[appium,easyocr]"
pip install optics-framework

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 68/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

androidandroid-tvapp-testingappiumblebluetoothbrowser-testingcomputer-visione2e-testingios

Quick Facts

Stars65
Forks22
LanguagePython
CategoryMCP Server
LicenseApache-2.0
Quality Score68/100
Open Issues68
Last Updated2026-11-06
Created2025-03-31
Platformsbrowser, mcp, python
Est. Tokens~18k

About optics-framework

Optics Framework Self-healing test automation for mobile, web, TV — and AI agents. One keyword engine. Six ways to drive it: CSV/YAML files, a Python SDK, Robot Framework, a REST API, an interactive terminal, or an MCP server your AI agent talks to. Documentation · Install · Getting Started · [Keyw

Compatible Skills

These tools work well together with optics-framework for enhanced workflows:

  • ai-phone — semantic(0.32)+complementary+rare_topics+same_lang+similar_pop+shared_platform (66%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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