embedding_similarity

shallow

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

Compute text similarity using local algorithms (Bag of Words, TF-IDF, Character N-grams). No API key needed — runs entirely in-process. NOT real embeddings: for true semantic similarity with vector embeddings, use run_semantic_tests with mode="embeddings" and your OpenAI API key. Supports single pair or batch mode with pipe-separated pairs. Useful for RAG retrieval testing, semantic search evaluation, and text deduplication.

100.0/100

1 trials · measured 8 days ago

embedding_similarity 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.

Embed this score

Available for every tool, scored or not — not a verification perk. Always links back to this page.

Vouch score: embedding_similarity
[![Vouch score](https://vouch.tools/api/tools/61d6f384-dde2-474f-b109-d5de7a7ef881/badge.svg)](https://vouch.tools/tools/61d6f384-dde2-474f-b109-d5de7a7ef881)
embedding_similarity — Vouch