Query the Reactome database (Analysis and Content Services). Use when the user asks about pathway analysis, gene list enrichment, retrieving results by token, finding unmapped or not-found identifiers, mapping identifiers, reaction participants (inputs, outputs), pathway hierarchy (including top-level pathways), diagram export, cross-reference mapping, or searching the knowledgebase.
86%
Does it follow best practices?
Run evals on this skill
Adds up to 20 points to the overall score
High
Do not use without reviewing
The skill handles credentials insecurely by requiring the agent to include secret values verbatim in its generated output. This exposes credentials in the agent’s context and conversation history, creating a risk of data exfiltration.
The skill shows CLI commands that require passing analysis "tokens" via a --token argument (placeholders like TOKEN), which would force an agent to embed secret token values verbatim into generated commands/outputs to retrieve or download results, creating an exfiltration risk.
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.
High: the runtime path performs GET/POST to Reactome endpoints and reads outsider-fetched JSON/text (`scripts/reactome_analysis.py` → `_CLIENT.fetch_text` / `fetch_bytes`, then `json.loads(result)` and `_write_output`), which can include arbitrary text fields that could be repackaged into the agent’s subsequent LLM context.
google-deepmind/science-skills
4de6786
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.