What problem does it solve? Manual security review of pull requests is slow and noisy, often flooding reviewers with false positives or flagging pre-existing issues that the PR author did not introduce. This Skill automates PR security review with confidence-based filtering so only high-signal findings are reported. ## Core Features & Use Cases - Confidence-Scored Findings: Scores each detected issue from 0-100 and filters results against a configurable threshold (default 80) to suppress false positives. - Git Blame Context: Distinguishes issues introduced by the current PR from pre-existing code using git blame, so authors are only flagged for their own changes. - Auto-Skip and Policy Support: Automatically skips drafts, bot PRs, merged PRs, and trivial diffs, and loads org-specific security rules from user, project, and local policy files. - Use Case: A reviewer runs the skill on PR #123; it fetches the diff via the GitHub CLI, scans for injection, XSS, secrets, and SSRF patterns, blames changed lines, and reports only two high-confidence issues introduced by the PR. ## Quick Start Ask the agent to run a security review on pull request 123 and report only high-confidence issues introduced by that PR.