multi-perspective-review

multi-perspective-review is a skill for Claude Code, Codex from baphuongna/pi-crew. It costs 16 tokens per session (1,511 once invoked), scanned A, original, MIT.

A code-review method that examines a change from several angles, including whether a simpler solution would work, whether it follows the request, and whether it is correct. The review produces evidence for the author to assess.

In plain words
What is it for?
Use it to review features, bug fixes, or pull requests for scope, correctness, edge cases, maintainability, and simpler alternatives.
Why use it?
It can reveal unnecessary complexity before time is spent reviewing every detail, while separate review passes make different kinds of problems easier to spot.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents.

Good fit Use it to review features, bug fixes, or pull requests for scope, correctness, edge cases, maintainability, and simpler alternatives.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/baphuongna/pi-crew/multi-perspective-review
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add baphuongna/pi-crew --skill multi-perspective-review
Clone the repo
git clone --depth 1 https://github.com/baphuongna/pi-crew

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for multi-perspective-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/baphuongna/pi-crew/multi-perspective-review/github.svg)](https://agentmods.dev/skills/baphuongna/pi-crew/multi-perspective-review)
Your own site
<a href="https://agentmods.dev/skills/baphuongna/pi-crew/multi-perspective-review"><img src="https://agentmods.dev/badge/skills/baphuongna/pi-crew/multi-perspective-review/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for multi-perspective-review

Your own site · 80×15
<a href="https://agentmods.dev/skills/baphuongna/pi-crew/multi-perspective-review"><img src="https://agentmods.dev/badge/skills/baphuongna/pi-crew/multi-perspective-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 16 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,511 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 2 findings, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium MCP Rug Pull · line 73
    npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.
    Fix: Pin the version: npx @scope/[email protected]
  • medium MCP Rug Pull · line 127
    npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.
    Fix: Pin the version: npx @scope/[email protected]
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00016 $0.01511
Opus 5 $0.00008 $0.00756
Sonnet 5 $0.00003 $0.00302
Haiku 4.5 $0.00002 $0.00151

Measured 10d ago against content hash bffcea67754c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

multi-perspective-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/multi-perspective-review/SKILL.md · 179 lines

How it starts

The opening of the file, as written. The whole thing — 179 lines — stays where its author put it; the contents beside it link to each section on GitHub.

multi-perspective-review

Core principle: review early, review often, and separate concerns. Reviewer output is evidence to evaluate, not an instruction to obey blindly.

Distilled from detailed reads of requesting-code-review, receiving-code-review, subagent review checkpoints, differential review, and specialized review-agent patterns.

Pre-review: Simpler Alternative Pass (Mandatory)

Before running any review passes, ask:

  1. Is there a simpler, smaller, or more elegant way to achieve the same goal?
    • Doing nothing (is the problem real and load-bearing?)
    • Using something that already exists in the codebase
    • A smaller change that solves 90% of the goal with 10% of the risk
    • Solving it at a different layer (config vs code, framework vs app)
  2. If a better alternative exists, surface it BEFORE the line-by-line review.
  3. Skip only if the user explicitly says "don't question scope."

This is the most valuable finding you can produce — surfacing unnecessary complexity before reviewing its details.

Review Passes

Run relevant passes separately:

  1. Spec compliance: Does the work match the request and nothing extra?
  2. Correctness: Are edge cases, state transitions, and failure paths right?
  3. Regression risk: Could config precedence, runtime defaults, or public APIs break?
  4. Security: Trust boundaries, path containment, prompt injection, secrets, permissions.
  5. Tests: Do tests assert the changed behavior and isolation concerns?
  6. Maintainability: Narrow diff, typed inputs, clear ownership, reversible changes.
  7. Operator experience: Error/status text, recovery hints, artifacts, logs.
  8. Compatibility: Windows paths, Node/Pi versions, CLI flags, legacy paths.

Finding Format

[severity] path:line or symbol
Issue: ...
Impact: ...
Fix: ...
Verification: ...

Severity:

  • critical: data loss, secret leak, arbitrary command/path escape, unusable default install;
  • high: broken core workflow, ownership bypass, persistent incorrect state;
  • medium: important regression, flaky test, confusing recoverable behavior;
  • low: polish, maintainability, docs.

Read the full file on GitHub · 179 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 10d ago First seen · 179 lines · 16 tokens per session scan A bffcea67754c

Subscribe to this mod's changes

multi-perspective-review is a skill published in the GitHub repository baphuongna/pi-crew (52 stars, last pushed 5d ago), licensed MIT. It adds 16 tokens to every session and 1,511 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.