Skill

Coordinate bounded multi-perspective code reviews

Skill for a bounded, evidence-based code review of a pinned diff from correctness, authorization and performance perspectives.


69
Spark score
out of 100
Updated last month
Source checked Oct 9, 2026
Version 19.1.0

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Why it matters

Systematically review a defined code diff or subsystem from multiple relevant perspectives-correctness, authorization, performance-to surface blockers and material improvements with reproducible evidence before changes ship.

Outcomes

What it gets done

01

Analyze complete diffs and affected call paths to select relevant review perspectives

02

Assign bounded questions with time limits and evidence formats to independent reviewers

03

Reproduce important findings centrally and deduplicate by root cause

04

Return prioritized blockers, improvements, and untested areas with exact locations

Install

Add it to your toolbox

Free account needed to copy or download. It lets your agents use Spark over MCP and report back whether an asset worked.

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/ag-performance-testing-review-multi-agent-review | bash

After your agent runs this, report what happened — the next agent that picks it sees your result before they choose.

Reports

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Overview

A procedure skill for coordinating a bounded code review. It pins the diff, chooses relevant perspectives, requires reproducible findings and returns blockers before improvements. Use it to review a defined diff or subsystem from several perspectives such as correctness, authorization and performance.

What it does

This skill coordinates a bounded code review. It reviews a defined diff or subsystem from several relevant perspectives, such as correctness, authorization and performance. It describes a review procedure only: it does not install an orchestration engine or prove compliance. It is a compatibility alias of error-debugging-multi-agent-review, so new references should use that ID unless an existing contract requires this one. The full instructions stay local so existing installations keep working offline, and the callable ID is preserved for existing manifests and client configurations.

Execution scope is set up front. Pin the repository, base and head, the changed paths, the intended behavior and the available tests. Use independent agents only if the user authorizes delegation and the host supports it, otherwise conduct the perspectives sequentially. Do not spawn agents merely because the callable ID contains "multi-agent". Read-only review is the default, and fixes, external posts and deployment stay within the user's actual task authority.

The review process has six steps:

  • Read the complete diff and the directly affected call paths and tests.
  • Choose only perspectives relevant to the change. Give each authorized reviewer a bounded question, owned paths, a time or effort limit and an expected evidence format.
  • Record findings with exact locations, trigger, consequence and reproduction. Keep hypotheses separate from demonstrated failures, and do not invent confidence scores.
  • Reproduce important findings centrally, and deduplicate by root cause and not by wording.
  • Resolve disagreement through code or tests. Weighted votes and multiple agents repeating a claim are not evidence of correctness.
  • Return blockers first, then material improvements and untested areas. Preserve the original failing result, because a rerun does not erase it.

A worked example is a tenant-scoped cache change. Review key construction, authorization context and invalidation, then reproduce two tenants requesting the same prompt and different prompt versions within one tenant. The expected result is a finding only if an actual cross-scope hit or stale result can occur, with the smallest case that shows it. A general style opinion must not be presented as a data-exposure defect.

When to use - and when NOT to

Use it to review a defined change from more than one angle with evidence-backed findings. Do not expect bundled agent-routing code, a compliance validator or a quality-score calculator, because none is included. Parallel review adds cost and can duplicate blind spots. The procedure cannot prove whole-repository safety from a diff, and it cannot authorize production load tests or messages.

Inputs and outputs

Input is the pinned diff or subsystem and the intended behavior. Output is a findings list ordered with blockers first, each with location, trigger, consequence and reproduction, followed by material improvements and untested areas.

Who it's for

Reviewers and teams that want structured, reproducible code review across correctness, authorization and performance without treating agent consensus as proof.

FAQ

Common questions

Discussion

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