interrogate
Use for "interrogate", "adversarial review", "multi-subagent review", "challenge this", "stress test this code", "find blind spots", or "tear this apart".
Skill by Luks3110
Install
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/luks3110-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 cases: testing, agent-building
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
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-subagent review", "challenge this", "stress test this code", "find blind spots", or "tear this apart". Multiple independent reviewers challenge changes from independent angles.
- License
- MIT
- Instructions
- 107 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 subagent type to adversarially review code changes. Each reviewer gets the same prompt and rubric. ZCode runs every subagent on the session model, so the adversarial signal comes from the reviewers' distinct postures and tool scopes (a reviewer type reads a diff differently than an architect type), not assigned personas. Agreement across independently spawned reviewers is high-confidence signal; single-reviewer 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 Agent tool. Use the `interrogate reviewers` list from `~/.zcode/pstack-roles.md` when present, one reviewer per entry, extending or shrinking the Reviewer A/B/C/D labels below to the configured entry count; otherwise use the table defaults. | Subagent | Default type | |----------|--------------| | Reviewer A | `code-reviewer` | | Reviewer B | `code-architect` | | Reviewer C | `poteto-agent` | | Reviewer D | `general-purpose` | For each reviewer: - `subagent_type`: the configured `interrogate reviewers` entry, or the table default with no configured line If a configured type is rejected as unresolvable when you try to spawn the subagent, check the valid types in the Agent tool's error message, pick the closest equivalent, spawn with the valid type, and open a separate PR to update the configured value or default table. Do not block the review on the type issue. Read `references/reviewer-prompt.md` and fill in the template with: 1. The stated intent 2. The diff or file contents 3. The review rubric from `references/rubric.md` 4. The code-quality lens from `references/code-quality-review.md` The same filled template goes to all reviewers, so every reviewer applies the code-quality lens. Each reviewer produces structured findings as described in the prompt template. ## Step 4, Synthesize As results come back, build a unified picture: 1. **Parse all findings** from the reviewers 2. **Identify consensus**. Findings raised by 2+ reviewers independently are highest signal. 3. **Identify single-reviewer findings**. Still worth reading, but weight accordingly. 4. **Deduplicate**. Different reviewers may describe the same issue differently. Merge these and note which reviewers raised it. 5. **Note disagreements**. If one reviewer flags something and another explicitly says the opposite, that's useful 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. Reviewers only see a slice of the codebase. You have the full context (the goal, the constraints, the timeline, which tradeoffs were already considered). Use that context aggressively. Categorize every finding using these buckets: - **Act on**. Real issues affecting correctness, security, or maintainability given the actual goals. These would block a real PR. - **Consider**. Legitimate points, but you're not sure they outweigh the cost of addressing them right now. Worth the user's attention. - **Noted**. Technically valid but not actionable. Context-dependent, premature optimization, or low-impact given the current stage. - **Dismissed**. Wrong, nitpicky, or missing context. Brief explanation why. For each finding, include: - Which reviewer(s) raised it - The category (act on / consider / noted / dismissed) - A one-line rationale for the categorization ## Output Format Present the verdict in this structure: ### Intent > [The stated intent paragraph from Step 2] ### Reviewers - Reviewer [label]: [subagent type], [N findings] (one bullet per reviewer) ### Act On [Findings that should be addressed. For each: description, which reviewers raised it, why it matters.] ### Consider [Findings worth thinking about. For each: description, which reviewers raised it, tradeoff involved.] ### Noted [Valid but low-priority. Brief list.] ### Dismissed [Rejected findings with brief rationale. This shows the user what was filtered out and why, so they can override your judgment if they disagree.] ### Agreement Map [Where did reviewers agree, where did they diverge, and what does the pattern of agreement/disagreement tell us?]
From Luks3110/pstack-zcode, MIT.
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Signals
- Stars
- 9
- Forks
- 2
- Open issues
- 0
- Last commit (this folder)
- Aug 20, 2026 (2 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/Luks3110/pstack-zcode
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from Luks3110
- 0.565score
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poteto's agent style for concise, detailed responses, deliberate subagents, unslopped prose, simple code, and verified work.
SkillBFreshness: B★ 9Claude Code +9 - 0.565score
architect
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Sketch types, signatures, and module structure before code, then stay in the loop while implementation fills in.
SkillBFreshness: B★ 9Claude Code +9 - 0.565score
create-verification-skill
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Cite this page
interrogate skill. Agent Mart. https://agentmart.dev/skills/luks3110-interrogate (last updated 2026-10-24)