chhoumann/t3-pstack/interrogate
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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.
Install
npx vskill@latest install chhoumann/t3-pstack/interrogateSKILL.md
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 response with delegate_task, one per entry on the interrogate reviewers line in the model sheet, labeled Reviewer A, B, and so on to match the entry count. If the sheet or that line is missing, use the table defaults.
| Subagent | Default model | |
|---|---|---|
| Reviewer A | claudeAgent/claude-opus-5-5 effort=xhigh | |
| Reviewer B | codex/gpt-6.1-sol reasoningEffort=xhigh | |
| Reviewer C | grok/grok-4.7 reasoningEffort=xhigh |
Each reviewer gets role: "review", a brief that says to inspect only and change no file, and target set from its configured entry, or from its table default when there is no configured line. Omit target for an auto or inherit-parent entry, so that reviewer runs on the parent model.
If delegate_task rejects a configured entry, run that reviewer on another target of the same family from orchestrator_capabilities and say so. A model's family is the first segment of its ID's last / part, such as claude, gpt, or grok, whatever provider instance serves it. With no family match, use Reviewer A's default. If it rejects a table default, spawn on the closest target of the same family from orchestrator_capabilities (prefer the same reasoning tier), and open a separate PR to update the default table. Do not block the review on the slug issue. Never treat an alias entry as a rejected slug or apply either fallback to it.
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. Pick each subagent's reasoning level and fast or standard speed for the job, per the Subagents section of the poteto-mode skill.
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.]
Models
Role defaults on T3, stamped from plugins/pstack/models.json. A role line in the model sheet overrides each one. The sheet is ~/.config/t3-pstack/models.md ($XDG_CONFIG_HOME/t3-pstack/models.md when that is set), one per machine, and /setup-pstack writes it. When it is missing, read t3-pstack-models.md in the host's config directory ($CLAUDE_CONFIG_DIR or ~/.claude on Claude Code, $CODEX_HOME or ~/.codex on Codex). An entry is <providerInstanceId>/<modelId> plus <optionId>=<value> pairs, and it maps onto delegate_task's target, with the provider instance as providerInstanceId, the model as model, and the pairs as options. It splits at its first /, so a model ID with its own /, such as OpenCode's <provider>/<model>, is written whole after it. Option IDs differ per provider, so take them from orchestrator_capabilities. inherit-parent or auto omits target.
- interrogate reviewers:
claudeAgent/claude-opus-5-5 effort=xhigh,codex/gpt-6.1-sol reasoningEffort=xhigh,grok/grok-4.7 reasoningEffort=xhigh
Security
- Security scanPassed, 90 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingplugins/pstack/skills/interrogate/SKILL.md
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Works with
Any agent vskill installs to: 56 targets in all. These 39 have a page on this site.
- Claude Code
- Cursor
- GitHub Copilot
- Windsurf
- Codex
- Gemini CLI
- Cline
- Amp
- Roo Code
- Goose
- Continue
- Kilo Code
- Junie
- Trae
- OpenHands
- Qwen Code
- AI Agent
- Tabnine Chat
- Sourcegraph Cody
- Amazon Q
- Firebase Genkit
- Sweep
- Devin
- Phind
- Mentat
- Claude Desktop
- Aider
- GPT Pilot
- Plandex
- bolt.new
- v0
- Replit Agent
- Anse
- TypingMind
- BetterChatGPT
- LibreChat
- Warp AI
- Pieces
- Fig AI
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