testland/elasticsearch-relevance-tests
Author search-engine relevance regression tests for Elasticsearch, OpenSearch, and Apache Solr. Core workflow on the Elasticsearch Ranking Evaluation API (`POST {index}/_rank_eval`) - judgment lists (query + expected docs at ranks), per-query metrics (Precision@K, Recall@K, MRR, DCG, ERR), reproducible test corpora; pair with Quepid + Splainer for interactive judgment authoring. Per-engine references cover the OpenSearch delta (Search Relevance Workbench, neural query DSL, hybrid BM25 + neural pipelines, ES-to-OS migration parity) and the Apache Solr delta (no _rank_eval: debugQuery score explain, LTR feature/model store REST, eDisMax qf/pf/mm tuning, external nDCG harness). Use before changing analyzers, synonyms, boosts, or query templates on an Elasticsearch, OpenSearch, or Solr index that serves user-facing search, so the NDCG / MRR baseline is captured first.
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Low
Low-risk findings worth noting
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
W011: Third-party content exposure detected (indirect prompt injection risk).
What this means
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Why it was flagged
SKILL.md’s runtime path builds and submits LLM-ingested `_rank_eval` requests from a user-provided judgment CSV/file (Step 1/Step 4 `load_judgments("tests/judgments.csv")`), where outsider-authored query text can be ingested without selecting a specific pre-approved item.
Where we found it
tests/judgments.csv
content-type · 6 sites
The plugin reads a local CSV judgment file containing query text, doc IDs, and ratings, and uses the query text to build _rank_eval requests or Solr queries.
- Audited
- Security analysis