analyze_responses

shallow

io.github.JcJamet/ia-qa-toolbox · Verify this server

Semantically analyze N already-produced model outputs for the SAME task (the MCP counterpart to the LLM Sandbox). Without a reference: computes consensus — pairwise cosine agreement, the most-representative output, and the outlier. With a `reference` (ground truth): also ranks every output by closeness (token cosine + ROUGE-L composite) and names the closest. Deterministic, no LLM, no key — gate-able in CI. You bring the outputs (2+). For a 2-way head-to-head with structural JSON diff use compare_responses instead.

100.0/100

1 trials · measured 56 days ago

analyze_responses scores 100.0/100 on Vouch's measured behaviour index, from 1 real invocation trials against io.github.JcJamet/ia-qa-toolbox, measured 25 Aug 2026 under methodology v0.2.0. Every measured component scored 100.

Component breakdown

ComponentWeightValue
Reliability35%not applicable
Schema integrity25%100.0
Failure behaviour15%not applicable
Latency15%not applicable
Concurrency10%not applicable

Tool details

Transport
remote
Credential class
open
Input schema
not declared
Output schema
not declared
Side-effect classification
unclassified

Score history

DayScoreTierMethodology
2026-08-25100.0shallowv0.2.0

Probe evidence

ProbeOutcomes
schema_integritypass: 1

Raw request/response logs are not archived yet — the outcome counts above are drawn directly from every recorded trial.

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Vouch score: analyze_responses
[![Vouch score](https://vouch.tools/api/tools/c3971834-c57e-48ab-a43a-a11f57bb63e3/badge.svg)](https://vouch.tools/tools/c3971834-c57e-48ab-a43a-a11f57bb63e3)
analyze_responses — Vouch