testland/visual-baseline-gate
Consumes pre-classified visual-diff JSON and a reviewer-signed acceptance log to produce a single go/no-go CI verdict for visual regression. Blocks when intentional baseline changes lack a non-author reviewer sign-off or when regressions are present, and emits a markdown + JSON artifact for the CI step. Use this skill when the gate's input is pre-classified diff data and the enforcement concern is reviewer approval, not when the goal is fanning out to multiple engines (use a multi-engine CI orchestrator for that).
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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
The required workflow reads the PR-branch `.visual-acceptance.yml` (outsider-authored by reviewers, not the PR author) and passes its free-text `reason` values into the LLM context via YAML parsing and printing/templating for `visual-gate.md` (scripts/run_visual_gate.py).
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- Security analysis