Analyze git diffs against main for SQL safety and trust boundary issues.
npx skills add https://github.com/umairinayat/Specter-AI --skill review-umairinayat
Please help me install this Agent Skill. Skill: review Source: https://github.com/umairinayat/Specter-AI/tree/main/.claude/skills/review Command: npx skills add https://github.com/umairinayat/Specter-AI --skill review-umairinayat
Pre-landing PR reviews often miss subtle SQL safety issues, data integrity risks, LLM prompt trust boundary violations, and unintended side effects in diffs. This Skill automates those checks against the main branch to reduce review toil and merge risk.
Run a pre-landing PR review on your feature branch to surface SQL, trust boundary, and side-effect issues before merging.
High-intent search queries and answers about installing and using this skill.
Pre-merge diff analysis checks the current git diff against the main branch to surface SQL injection risks and unsafe data writes before merging. It targets SQL safety by flagging potential injection vectors across the diff for actionable feedback.
Diff-based safety analysis detects LLM trust boundary violations by flagging prompt leakage, unsafe model configurations, and boundary risks across the PR diff before merge. It validates trust boundaries to prevent unintended prompt exposure in production.
Analyzing the feature branch diff against main identifies unintended side effects and data integrity risks by detecting conditional side effects, missing validations, and risky code patterns. This structural consistency check reduces merge risk and review toil.
Pre-landing PR checks operate with no listed dependencies, running diff analysis directly against your main branch. You can integrate the structured feedback report into a standard review toolkit without installing external packages.
Diff-based PR analysis catches subtle SQL safety issues, data integrity risks, LLM prompt trust boundary violations, and unintended side effects across diffs that manual reviews often miss. It automates safety checks to reduce review toil and merge risk.
Automated diff analysis targets SQL safety, data integrity, and LLM trust boundaries, but does not replace human judgment for complex business logic or architectural decisions. Use it to surface critical issues, not as the sole merge gate for high-risk changes.
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