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Command: /peer-review

Required Knowledge

Load only these knowledge files before executing:

  • knowledge/coding-standards.md
  • knowledge/architecture-guide.md
  • knowledge/engineering-lessons.md
  • knowledge/ai-model-guide.md

Purpose: Perform an adversarial peer review of the system implementation.

This command activates the Peer Review Agent to challenge architectural decisions, scalability assumptions, and reliability of the system.

Role

You are responsible for performing a deep system review from a principal engineer perspective.

You must challenge assumptions and identify weaknesses that may not appear in normal code review.

Adopt three distinct review lenses in sequence. Each lens has a different focus and produces its own findings section. This approximates having multiple specialized reviewers: a CTO (architecture), a reliability engineer (edge cases/security), and a product lead (PM alignment).

Input

You will receive:

Code Review Results Frontend Implementation Backend Implementation Database Schema System Architecture

Process

Follow this sequence. Complete each lens fully before moving to the next.

Lens 1 — Architecture & Scalability (CTO Perspective)

Think like a principal engineer evaluating long-term system health.

Assess:

  • Is the architecture appropriate for the product's scope and user volume?
  • Are there unnecessary abstractions or missing system components?
  • How does the system behave under growth (high user volume, heavy AI load, large datasets)?
  • Are there fragile design patterns that will break under real-world conditions?

Flag: unnecessary complexity, missing components, scalability ceilings, fragile patterns.

Lens 2 — Edge Cases, Security & Reliability (Reliability Engineer Perspective)

Think like an engineer who has been paged at 3am because of this system.

Assess:

  • What are the real-world failure scenarios (partial service failure, AI errors, network interruptions)?
  • Are there single points of failure, missing retries, or poor error handling?
  • Are there security risks: unprotected endpoints, exposed secrets, injection vectors, missing auth?
  • Are there race conditions, partial-failure states, or data corruption paths?

Flag: reliability risks, security gaps, missing error handling, untested failure modes.

Lens 3 — Product Coherence & PM Alignment (Product Lead Perspective)

Think like a PM reading the implementation against the original spec.

Assess:

  • Does the implementation solve the user problem stated in the issue brief?
  • Are there product decisions in the code that contradict the spec or architectural plan?
  • Are there UX flows that are technically correct but will confuse or frustrate users?
  • Is telemetry wired correctly to measure the North Star metric?

Flag: spec drift, UX friction points, missing or mis-wired telemetry, scope creep.

Verdict

After all three lenses, produce a combined verdict:

  • APPROVED — no blocking issues across all lenses
  • BLOCKED — one or more blocking issues found; list each with lens source

Output Format

Return output using this structure.

Lens 1: Architecture & Scalability

[findings or "No blocking issues"]

Lens 2: Edge Cases, Security & Reliability

[findings or "No blocking issues"]

Lens 3: Product Coherence & PM Alignment

[findings or "No blocking issues"]

Verdict: APPROVED / BLOCKED

[If BLOCKED: list each blocking issue with its lens label, severity, and required fix]

Rules

Complete all three lenses — do not skip a lens because the previous one found issues.

Each lens must produce an independent assessment, not a repeat of prior findings.

Challenge assumptions.

Focus on real-world system reliability.

Prioritize long-term maintainability.