git:20261008.5062f28 to git:20261013.058a348

23 added, 58 removed. Audit A to A.

---

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."

---

# Interrogate

On Codex, read the [platform mapping](../poteto-mode/references/codex-tools.md), including its per-skill notes, before following this skill.

On GitHub Copilot, read the [platform mapping](../poteto-mode/references/copilot-tools.md), including its per-skill notes, before following this skill.

- 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.

- The deliverable is a synthesized verdict. Do NOT auto-apply changes.

+ 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, Determine Scope

+ ## 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) plus any surrounding context files the reviewers need to understand the code.

- ## Step 2, State the Intent

+ - 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.

- Before spawning reviewers, state the intent explicitly. Derive this from:

+ Package the diff or file contents with any surrounding context files the reviewers need to understand the code.

- - The user's message

- - Commit messages

- - PR description if one exists

- - The code itself

+ ## Step 2, Intent

- Write one clear paragraph. If you're unsure about the intent, ask the user before proceeding.

+ 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 using the `Agent` tool. Use the `interrogate reviewers` line in the `pstack-models.md` override sheet (`/setup-pstack` lists its path per runtime), one reviewer per entry, extending or shrinking the Reviewer labels below to the configured entry count. If the sheet or that line is missing, use the table defaults.

+ Launch all reviewers in a single message with the `Agent` tool, one per entry on the `interrogate reviewers` line in `pstack-models.md`, 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 | `opus` |

| Reviewer B | `fable` |

| Reviewer C | `sonnet` |

| Reviewer D | `haiku` |

- For each reviewer:

- - `subagent_type`: `general-purpose`

- - `model`: the configured `interrogate reviewers` entry, or the table default with no configured line. For an `auto` or `inherit-parent` entry, omit `model` so that reviewer runs on the parent model.

- - `readonly`: `true`

- If the `Agent` tool rejects a configured entry, run that reviewer on the table default of its family and say so. Families go by model name, such as Opus, Fable, or Sonnet. With no family match, use Reviewer A's default. If it rejects a table default, check the valid slugs in the `Agent` tool's error message, pick the closest equivalent (prefer the same family and reasoning tier), spawn with it, 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.

+ Each reviewer gets `subagent_type: "general-purpose"`, `readonly: true`, 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.

- 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`

+ If the `Agent` tool rejects a configured entry, run that reviewer on its family's table default and say so. Families go by model name, such as Opus, Fable, or Sonnet. With no family match, use Reviewer A's default. If it rejects a table default, spawn with the closest equivalent from the valid slugs in its error message (prefer the same family and 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.

- The same filled template goes to all reviewers, so every model applies the code-quality lens.

+ 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:

- 1. **Parse all findings** from the reviewers

- 2. **Identify consensus**. Findings raised by 2+ models independently are highest signal.

- 3. **Identify lone-model findings**. Still worth reading, but weight accordingly.

- 4. **Deduplicate**. Different models may describe the same issue differently. Merge these and note which models raised it.

- 5. **Note disagreements**. If one model flags something and another explicitly says the opposite, that's useful context for the verdict.

+ 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.

- 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.

+ 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.

- For each finding, include:

- - Which model(s) raised it

- - The category (act on / consider / noted / dismissed)

- - A one-line rationale for the categorization

+ - **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

- Present the verdict in this structure:

### Intent

> [The stated intent paragraph from Step 2]

### Reviewers

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

### Act On

- [Findings that should be addressed. For each: description, which models raised it, why it matters.]

+ [Each: description, which models raised it, why it matters.]

### Consider

- [Findings worth thinking about. For each: description, which models raised it, tradeoff involved.]

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

### Noted

- [Valid but low-priority. Brief list.]

+ [Brief list.]

### Dismissed

- [Rejected findings with brief rationale.]

+ [Each with a brief rationale.]

### Agreement Map

- [Where did models agree, where did they diverge, and what does the pattern of agreement/disagreement tell us?]

+ [Where models agreed and diverged, and what that pattern tells us.]

## Reasoning effort

A role value in the override sheet may name a reasoning effort after its model, as in `opus @xhigh`. Levels on Claude Code: `low`, `medium`, `high`, `xhigh`, `max`. Which ones apply depends on the model. A value without `@` takes the sheet's `default effort` line, a level or `session`, and `session` when the sheet has no such line. `session` sets no effort, so the dispatch is the usual one. Strip the suffix before reading the model: `inherit-parent` or `auto` still omits `model` at every level, and a model name is passed as `model`. On Claude Code, a level picks the effort agent from the `subagent_type` you would otherwise use. `pstack:poteto-agent` becomes `subagent_type: "pstack:poteto-agent-<level>"`. `general-purpose`, or no `subagent_type`, becomes `subagent_type: "pstack:effort-<level>"`. The effort agents set only `effort`, so the model you pass still decides the model. On Codex, pass the level as `spawn_agent`'s `reasoning_effort` and keep the usual instructions.