interrogate

Solid

Use for "interrogate", "adversarial review", "multi-model review", "challenge this", "stress test this code", "find blind spots", or "tear this apart". Multiple LLM reviewers challenge changes from independent angles.

AI & Automation 122 stars 8 forks Updated today MIT

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Skill Content

# Interrogate Spawn one reviewer per configured model to adversarially review code changes. Each model gets the same prompt and rubric. The adversarial signal comes from model diversity, not assigned personas. Models differ in blind spots, priors, and reasoning patterns. Agreement across models is high-confidence signal; lone-model findings are worth reading but lower confidence. The deliverable is a synthesized verdict. Do NOT auto-apply changes. ## Step 1, Determine Scope Identify what to review from context: - If the user points at specific files or a diff, use that - If on a feature branch, run `git diff main...HEAD` (or the appropriate base branch) for the full changeset - If the user's message references recent work, gather the relevant files Package the diff (or file contents) plus any surrounding context files the reviewers need to understand the code. ## Step 2, State the Intent Before spawning reviewers, state the intent explicitly. What is this code trying to accomplish? Derive this from: - The user's message - Commit messages - PR description if one exists - The code itself Write one clear paragraph. Reviewers challenge whether the work achieves the intent well, not whether the intent itself is correct. If you're unsure about the intent, ask the user before proceeding. ## Step 3, Spawn Reviewers Launch all reviewers in a single message using the Task tool. Spawn one reviewer per Reviewer A/B/C/D label below. Vary the `model` between them where the Agen...

Details

Author
Sma1lboy
Repository
Sma1lboy/rove
Created
4 months ago
Last Updated
today
Language
TypeScript
License
MIT

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