{"id":43769293,"url":"https://github.com/agentgram/ax-score","last_synced_at":"2026-02-05T16:10:04.585Z","repository":{"id":336279694,"uuid":"1149032758","full_name":"agentgram/ax-score","owner":"agentgram","description":"AX Score - The Lighthouse for AI Agent Experience. 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[DONE]\nRunning 24 audits... [DONE]\n\nAX Score for https://agentgram.co\n---------------------------------\nOverall Score: 94/100\n\nCategories:\n- Discovery: 100/100\n- API Quality: 92/100\n- Structured Data: 100/100\n- Auth \u0026 Onboarding: 85/100\n- Error Handling: 100/100\n- Documentation: 100/100\n\nTop Suggestions:\n- [Auth] Implement Ed25519 cryptographic signatures for higher security.\n- [API] Add X-RateLimit-Reset headers to all responses.\n```\n\n---\n\n## 📦 Installation\n\n### CLI Usage\n\nInstall globally:\n\n```bash\nnpm install -g @agentgram/ax-score\n```\n\nOr run directly with npx:\n\n```bash\nnpx @agentgram/ax-score https://example.com\n```\n\n### Programmatic Usage\n\n```typescript\nimport { runAudit } from '@agentgram/ax-score';\n\nconst results = await runAudit('https://example.com');\nconsole.log(`Score: ${results.score}`);\n```\n\n---\n\n## 📊 AX Categories\n\n| Category          | Weight | Description                                                              |\n| ----------------- | ------ | ------------------------------------------------------------------------ |\n| Discovery         | 25%    | Can agents find your API and documentation? (`llms.txt`, `openapi.json`) |\n| API Quality       | 25%    | Is the API consistent and easy to use programmatically?                  |\n| Structured Data   | 20%    | Does the site provide JSON-LD or other machine-readable metadata?        |\n| Auth \u0026 Onboarding | 15%    | Can agents register and authenticate without human intervention?         |\n| Error Handling    | 10%    | Are errors structured and actionable for autonomous systems?             |\n| Documentation     | 5%     | Is there comprehensive, machine-readable documentation?                  |\n\n---\n\n## 🎯 Scoring\n\nax-score uses a 0-100 scale inspired by Google Lighthouse. Scores are calculated as a weighted arithmetic mean of individual audit results.\n\n- 🟢 **90-100**: Excellent (Agent-Ready)\n- 🟡 **50-89**: Needs Improvement\n- 🔴 **0-49**: Poor (Agent-Hostile)\n\n---\n\n## 🛣️ Roadmap\n\n- **Phase 1: CLI (Current)** — Core gathering and auditing engine with terminal output.\n- **Phase 2: Web UI** — A hosted version to test sites and share reports.\n- **Phase 3: CI/CD** — GitHub Action to track AX scores over time.\n- **Phase 4: Live Testing** — Real-world agent interaction testing.\n\n---\n\n## 🤝 Contributing\n\nWe welcome contributions! Please see [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines on how to add new audits or gatherers.\n\n---\n\n## 🔗 Related\n\n- **[AgentGram](https://github.com/agentgram/agentgram)** — The social network for AI agents.\n- **[AX Principles](docs/AX_PRINCIPLES.md)** — The definitive guide to building agent-friendly platforms.\n\n---\n\n## 📄 License\n\nMIT License. See [LICENSE](LICENSE) for details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fagentgram%2Fax-score","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fagentgram%2Fax-score","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fagentgram%2Fax-score/lists"}