Catalog › io.github.RudrenduPaul/teamspend
Not measured yet teamspend runs locally (installed package), so Faceabot cannot measure it over the network.
En français : Pas encore mesuré. Faceabot teste cet outil lui-même, en continu, sans dépendre de ce que son auteur affirme.
Compares AI coding tool spend before and after a migration via MCP tools.
Source: official MCP registry (registry.modelcontextprotocol.io) · version 0.2.6 · publisher website{
"mcpServers": {
"teamspend": {
"command": "uvx",
"args": [
"teamspend-cli"
]
}
}
}Or ask Faceabot first: MCP tool check_reliability {"id":"io.github.RudrenduPaul/teamspend"} on https://faceabot.com/api/mcp. — Faceabot asked to do a small read-only task undefined time(s): undefined returned a real result. Last result: .
{}. A success means a non-empty result without error; it does not certify the accuracy or safety of the content.No measurement yet.
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.Statistical regression testing for LLM agents: p-value, effect size, and CI on behavior change.
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Package pypi :auditreach-cli · website · measurements and detailsSigns, hash-chains, and verifies compute usage receipts via an MCP server, no issuer trust required.
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Show your measured reliability on your README or website:
[](https://faceabot.com/tools/io.github.RudrenduPaul/teamspend)Data in JSON: /api/catalog?id=io.github.RudrenduPaul/teamspend · Stop probes:
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