Submit compact Bgee SPARQL requests for healthy wild-type expression metadata and ontology-aware lookup patterns. Use when a user wants concise Bgee summaries; save raw results only on request.
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Low
Low-risk findings worth noting
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
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.
The required workflow runs `scripts/sparql_request.py`, which fetches public SPARQL results from `ENDPOINT = https://www.bgee.org/sparql/` via `requests.get/requests.post`, then turns `response.text` / `response.json()` fields into LLM-visible `summary`/`text_head` content—so outsider-authored free text from a public web source can enter the agent context indirectly.
11c74d6
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