Authors a new Instance AI workflow eval case — written locally as JSON, calibrated against a real build, then pushed to the LangTracer suite CI runs — build cases, behaviour/process cases, credential cases, and seeded (mid-conversation) cases — with intent-driven expectations. Use when adding or changing an Instance AI workflow eval, or debugging why one is flaky.
Security
1 high severity finding. You should review these findings carefully before considering using this skill.
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 explicitly tells the agent to hand the driver the login credentials (and even embeds a plaintext default password), which requires outputting secret values verbatim.
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.
In SKILL.md step 5/6, the runtime reads the built workflow and the HTML report transcript produced by the eval run, but it does not describe ingesting any outsider-authored free text from an external queue/feed/email/chat/GitHub issue/Jira ticket; the only free-text inputs are the eval case’s own `conversation`/`dataSetup` authored by the driver and (optionally) LangSmith `seedThread` content fetched by opaque threadId.
bcbea0a
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.