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Is SparkVibeAI Spec Committee reliable?

Not measured yet Not measured yet. Faceabot will test it automatically; you can speed this up with the MCP tool check_reliability.

En français : Pas encore mesuré. Faceabot teste cet outil lui-même, en continu, sans dépendre de ce que son auteur affirme.

What it does

Commission a multi-model AI spec committee from your agent; get rubric-scored, build-ready specs.

Source: official MCP registry (registry.modelcontextprotocol.io) · version 1.1.0 · publisher website
Connect your agent
{
  "mcpServers": {
    "spec-committee": {
      "url": "https://api.sparkvibeai.com/mcp"
    }
  }
}
Or ask Faceabot first: MCP tool check_reliability {"id":"com.sparkvibeai/spec-committee"} on https://faceabot.com/api/mcp.
Does it actually do the job?

Not tested with a real task yet. Faceabot only runs real tasks on tools that declare themselves read-only (readOnlyHint), with a neutral sample input.

Faceabot measurements

No measurement yet.

Method: MCP initialize then tools/list from Faceabot (FaceabotProbe/1.0), plus one read-only tool call with a neutral input when the server declares one, repeated over time. This checks that the server is up and speaks MCP correctly; it does not certify the quality or safety of each tool. How measurement works.

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Publisher of SparkVibeAI Spec Committee?

Show your measured reliability on your README or website:

Faceabot reliability badge for SparkVibeAI Spec Committee

[![Measured by Faceabot](https://faceabot.com/badge/com.sparkvibeai/spec-committee.svg)](https://faceabot.com/tools/com.sparkvibeai/spec-committee)
Data in JSON: /api/catalog?id=com.sparkvibeai/spec-committee · Stop probes: POST /api/reliability/opt-out

AI agents: all of this is available without keys over MCP https://faceabot.com/api/mcp · HTTP https://faceabot.com/api/catalog?q=… · Guide : llms.txt

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