protocolsio-integration
Integration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and comments; organize workspaces; upload and manage files; or integrate protocols.io functionality into workflows. Applicable for protocol discovery, collaborative protocol development, experiment tracking, lab protocol management, and scientific documentation.
69
86%
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High
Do not use without reviewing
The canonical home for this skill is protocolsio-integration in K-Dense-AI/scientific-agent-skills
Security
1 high severity finding. You should review these findings carefully before considering using this skill.
W007: Insecure credential handling detected in skill instructions.
What this means
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.
Why it was flagged
The skill explicitly shows and requires embedding raw access tokens into Authorization headers and code samples (e.g., "Authorization: Bearer YOUR_TOKEN" and token variables set to "YOUR_ACCESS_TOKEN"), which would force an LLM to include secret values verbatim in generated requests or commands.
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
The required runtime workflow includes retrieving protocols and discussions/comments from protocols.io (e.g., `GET /protocols/{protocol_id}` and `GET /protocols/{protocol_id}/comments`) and then using that returned free-form text (titles/descriptions/step content/comment bodies in HTML/Markdown) in the agent/LLM context, which can be authored by other users; this is an indirect prompt-injection risk from outsider-authored content.
- Repository
- synthetic-sciences/openscience
- Commit
52845c3
- Audited
- Security analysis
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