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interrogate

Use for "interrogate", "adversarial review", "multi-model review", "challenge this", "stress test this code", "find blind spots", or "tear this apart".

Skill by MatrixMagician

IndexedMIT
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/matrixmagician-interrogate

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

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.

Use cases: testing, ml

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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/interrogate

What's inside

Skill name
interrogate
Description
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.
License
MIT
Instructions
73 lines in SKILL.md · view on GitHub

Files (5)

  • SKILL.md
  • code-quality-review.md · references/
  • lead-judgment.md · references/
  • reviewer-prompt.md · references/
  • rubric.md · references/

SKILL.md (first lines)

# Interrogate

Spawn one reviewer per configured model to adversarially review code changes. The adversarial signal comes from model diversity, not assigned personas. The deliverable is a synthesized verdict. Do NOT auto-apply changes.

## Step 1, 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 with any surrounding context files the reviewers need to understand the code.

## Step 2, Intent

Before spawning reviewers, state the intent in one clear paragraph from the user's message, commit messages, the PR description if one exists, and the code. If you're unsure about the intent, ask the user before proceeding.

## Step 3, Spawn Reviewers

Launch all reviewers in a single message with the Agent tool, one per entry on the `interrogate reviewers` line in `.claude/rules/mstack-models.md`, labeled Reviewer A, B, C, and so on to match the entry count. If the file or that line is missing, use the table defaults. Set `effort` per **Effort by tier** in [`poteto-mode`](../poteto-mode/SKILL.md).

| Subagent | Default model |
|----------|---------------|
| Reviewer A | `fable` |
| Reviewer B | `opus` |
| Reviewer C | `sonnet` |

The three seats are one family, so the rubric differentiation in `references/rubric.md` is carrying more weight here than it did upstream, where seats came from different labs. Keep the personas sharply distinct, and keep the tiers spread, which varies `effort` through the tier table. A panel of three identical seats is one reviewer with extra steps.

Each reviewer gets `subagent_type: general-purpose` and `model` set to its configured entry, or its table default when there is no configured line. Omit `model` for an `auto` or `inherit-parent` entry, so that reviewer runs on the parent model. Each reviewer takes a read-only posture. Instruct it to read and report, never write. Claude Code has no readonly flag, so the constraint lives in the prompt.

The defaults are tier aliases, so they resolve for every user and do not go stale. If the Agent tool rejects a configured entry, run that reviewer on its table default and say so in the report. Do not block the review on it. Never treat an `auto` or `inherit-parent` entry as a rejected value.

Read `references/reviewer-prompt.md` and fill in the same template for every reviewer with the stated intent, the diff or file contents, the rubric from `references/rubric.md`, and the code-quality lens from `references/code-quality-review.md`.

## Step 4, Synthesize

As results come back, build a unified picture. Parse every reviewer's findings. Merge findings that describe the same issue differently, and note which models raised each one. Findings two or more models raised independently are the highest signal. Read a lone model's finding, but weight it accordingly. Note disagreements. If one model flags something and another explicitly says the opposite, that is context for the verdict.

## Step 5, Lead Judgment

You are the lead reviewer, a pragmatic senior engineer, not a neutral aggregator. Read `references/lead-judgment.md` for the full framework. Put every finding in one of four buckets, with the model(s) that raised it and a one-line rationale.

- **Act on**. Real issues affecting correctness, security, or maintainability given the actual goals. They would block a real PR.
- **Consider**. Legitimate, but you're not sure they outweigh the cost of addressing them now. Worth the user's attention.
- **Noted**. Technically valid but not actionable. Context-dependent, premature optimization, or low-impact at this stage.
- **Dismissed**. Wrong, nitpicky, or missing context, with a brief reason.

## Output Format

### Intent
> [The stated intent paragraph from Step 2]

### Reviewers
- Reviewer [label]: [model name], [N findings] (one bullet per reviewer)

### Act On
[Each: description, which models raised it, why it matters.]

### Consider
[Each: description, which models raised it, the tradeoff.]

### Noted
[Brief list.]

### Dismissed
[Each with a brief rationale.]

### Agreement Map
[Where models agreed and diverged, and what that pattern tells us.]

From MatrixMagician/mstack, MIT.

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Last commit (this folder)
Oct 17, 2026 (11 days ago)
Last release
Aug 20, 2026 (2 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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interrogate skill. Agent Mart. https://agentmart.dev/skills/matrixmagician-interrogate (last updated 2026-10-24)