{"id":"c2e17ae9-daff-4fa2-b83f-a6c54655013f","slug":"clawhub-skills-adityak6798-website-usability-test-nova-act","name":"nova-act-usability","description":"AI-orchestrated usability testing using Amazon Nova Act. The agent generates personas, runs tests to collect raw data, interprets responses to determine goal achievement, and generates HTML reports. Tests real user workflows (booking, checkout, posting) with safety guardrails. 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The agent generates personas, runs tests to collect raw data, interprets responses to determine goal achievement, and generates HTML reports. Tests real user workflows (booking, checkout, posting) with safety guardrails. Use when asked to \"test website usability\", \"run usability test\", \"generate usability report\", \"evaluate user experience\", \"test checkout flow\", \"test booking process\", or \"analyze website UX\".","source":"CLAWHUB","sourceId":"clawhub:skills:adityak6798:website-usability-test-nova-act","repository":"https://github.com/openclaw/skills/tree/main/skills/adityak6798/website-usability-test-nova-act","documentation":"https://www.xpersona.co/agent/clawhub-skills-adityak6798-website-usability-test-nova-act","protocols":["OPENCLEW"],"capabilities":["analyze","adapt","ask","trigger","reason","you","take"],"languages":["typescript"],"examples":[{"kind":"example","language":"python","snippet":"import subprocess\nimport os\nimport sys\nimport json\nimport tempfile\n\n# Step 1: Check dependencies\ntry:\n    import nova_act\n    print(\"✅ Dependencies ready\")\nexcept ImportError:\n    print(\"📦 Dependencies not installed. Please run:\")\n    print(\"   pip3 install nova-act pydantic playwright\")\n    print(\"   playwright install chromium\")\n    sys.exit(1)\n\n# Step 2: Verify Nova Act API key\nconfig_file = os.path.expanduser(\"~/.openclaw/config/nova-act.json\")\nwith open(config_file, 'r') as f:\n    config = json.load(f)\n    if config.get('apiKey') == 'your-nova-act-api-key-here':\n        print(f\"⚠️  Please add your Nova Act API key to {config_file}\")\n        sys.exit(1)\n\n# Step 3: YOU (the AI agent) generate personas\n# Example for https://www.pgatour.com/ (golf tournament site)\nwebsite_url = \"https://www.pgatour.com/\"\n\npersonas = [\n    {\n        \"name\": \"Marcus Chen\",\n        \"archetype\": \"tournament_follower\",\n        \"age\": 42,\n        \"tech_proficiency\": \"high\",\n        \"description\": \"Avid golf fan who follows multiple tours and tracks player stats\",\n        \"goals\": [\n            \"Check current tournament leaderboard\",\n            \"View recent tournament results\",\n            \"Track favorite player performance\"\n        ]\n    },\n    {\n        \"name\": \"Dorothy Williams\",\n        \"archetype\": \"casual_viewer\",\n        \"age\": 68,\n        \"tech_proficiency\": \"low\",\n        \"description\": \"Occasional golf viewer who watches major tournaments\",\n        \"goals\": [\n            \"Find when the next tournament is\",\n            \"See who won recently\",\n            \"Understand how to watch online\"\n        ]\n    }\n]\n\n# Step 4: Save personas and run test\nwith tempfile.NamedTemporaryFile(mode='w', suffix='.json', delete=False) as f:\n    json.dump(personas, f, indent=2)\n    personas_file = f.name\n\nskill_dir = os.path.expanduser(\"~/.openclaw/skills/nova-act-usability\")\ntest_script = os.path.join(skill_dir, \"scripts\", \"run_adaptive_test.py\")\n\n# Run with AI-generated personas\nsubprocess.run([sys"},{"kind":"example","language":"json","snippet":"{\n  \"name\": \"FirstName LastName\",\n  \"archetype\": \"descriptive_identifier\",\n  \"age\": 30,\n  \"tech_proficiency\": \"low|medium|high\",\n  \"description\": \"One sentence about who they are\",\n  \"goals\": [\n    \"First goal relevant to this website\",\n    \"Second goal relevant to this website\",\n    \"Third goal relevant to this website\"\n  ]\n}"}]}}