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    "name": "Dify",
    "score": 2.9,
    "stars": 158030,
    "repo": "langgenius/dify",
    "created": "2023"
   },
   {
    "id": "langflow",
    "name": "Langflow",
    "score": 3.0,
    "stars": 155567,
    "repo": "langflow-ai/langflow",
    "created": "2023"
   },
   {
    "id": "open-webui",
    "name": "Open WebUI",
    "score": 3.5,
    "stars": 154145,
    "repo": "open-webui/open-webui",
    "created": "2023"
   }
  ],
  "top10_mean": 3.08,
  "top10_above_mean": 5,
  "top25_mean": 3.11,
  "big_tech": {
   "n": 45,
   "mean": 3.38,
   "median": 3.2,
   "at_least_5": 5,
   "max": 6.4
  },
  "everyone_else": {
   "n": 211,
   "mean": 3.09,
   "median": 3.0
  },
  "by_year": [
   {
    "n": 19,
    "mean": 3.52,
    "median": 3.4,
    "year": "2022 or earlier"
   },
   {
    "n": 57,
    "mean": 2.89,
    "median": 2.8,
    "year": "2023"
   },
   {
    "n": 46,
    "mean": 3.19,
    "median": 3.0,
    "year": "2024"
   },
   {
    "n": 97,
    "mean": 3.22,
    "median": 3.1,
    "year": "2025"
   },
   {
    "n": 37,
    "mean": 3.04,
    "median": 2.9,
    "year": "2026"
   }
  ]
 },
 "top_scores": [
  {
   "name": "Cynative",
   "score": 8.4,
   "category": "cybersecurity",
   "id": "cynative"
  },
  {
   "name": "Local Deep Researcher",
   "score": 7.1,
   "category": "ai_assistants",
   "id": "local-deep-researcher"
  },
  {
   "name": "Coroot (MCP server and AI RCA)",
   "score": 6.7,
   "category": "infrastructure_ops",
   "id": "coroot"
  },
  {
   "name": "Context7",
   "score": 6.5,
   "category": "coding",
   "id": "context7"
  },
  {
   "name": "GitHub MCP Server",
   "score": 6.4,
   "category": "coding",
   "id": "github-mcp-server"
  },
  {
   "name": "Google Analytics MCP",
   "score": 6.4,
   "category": "data_analytics",
   "id": "google-analytics-mcp"
  },
  {
   "name": "AgentGPT",
   "score": 6.3,
   "category": "ai_assistants",
   "id": "agentgpt"
  },
  {
   "name": "AI Town",
   "score": 6.2,
   "category": "agent_frameworks",
   "id": "ai-town"
  },
  {
   "name": "GitHub Agentic Workflows",
   "score": 6.2,
   "category": "coding",
   "id": "gh-aw"
  },
  {
   "name": "Perplexity MCP Server",
   "score": 6.2,
   "category": "ai_assistants",
   "id": "perplexity-mcp"
  }
 ],
 "key_numbers": [
  "We scored 256 open-source AI agents on how well their own code limits the damage when something goes wrong. The average was 3.1 out of 10.",
  "91% scored below 5. Only two scored 7 or higher.",
  "In 64% of agents, a prompt injection could get the agent to leak data and do something irreversible without anyone approving it, on default settings.",
  "98% break Meta's Agents Rule of Two. Within one session they can process untrustworthy inputs, have access to sensitive systems or private data, and change state or communicate externally. The rule allows no more than two of the three.",
  "Prompt injection is where agents are weakest. They earned 15% of the available points there, and 39% earned none.",
  "53% already have a safeguard in their code that is turned off by default.",
  "Of the agents that run code, 63% do it without a sandbox unless the user sets one up.",
  "Popularity doesn't help. The 10 most-starred agents average 3.1, about the same as the rest. OpenClaw, the most-starred agent we scored (392k GitHub stars), got 2.8.",
  "Agents from big tech companies did only slightly better: 3.38 on average, against 3.09 for everyone else."
 ]
}