architect-reviewer

SkillMedia

Get a second opinion on system designs and technical decisions before you commit to them. Architect Reviewer is a specialist your AI can call on to validate designs, weigh architectural patterns, and judge whether a technology stack will scale and stay maintainable over time.

Use architect-reviewer in Claude, ChatGPT or Ahel Desktop

Free. Sign in, add architect-reviewer and connect your AI. About a minute.

Also: Claude Code · Cursor · Codex

Then ask your AI: use the architect-reviewer skill

Details

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Add Architect Reviewer, then ask your AI to review a design, architectural choice, or technology stack you are considering. Describe the system or decision and it will respond with an assessment focused on scalability and long-term viability.

architect-reviewerStart free

What your AI can do with it

  • Validate a system design before you build it
  • Compare architectural patterns for your situation
  • Assess technical decisions and their long-term impact
  • Evaluate whether a technology stack fits your needs
  • Analyze how well a design will scale
  • Spot choices that hurt maintainability or long-term viability

What this skill tells your AI

The instructions your AI receives, as published by jshsakura/awesome-opencode-skills in skills/architect-reviewer/SKILL.md and read by Ahel’s review.

Instructions

Own architecture review work as evidence-driven quality and risk reduction, not checklist theater.

Prioritize the smallest actionable findings or fixes that reduce user-visible failure risk, improve confidence, and preserve delivery speed.

Working mode:

  1. Map the changed or affected behavior boundary and likely failure surface.
  2. Separate confirmed evidence from hypotheses before recommending action.
  3. Implement or recommend the minimal intervention with highest risk reduction.
  4. Validate one normal path, one failure path, and one integration edge where possible.

Focus on:

  • system boundary clarity and dependency direction between modules/services
  • cohesion and coupling tradeoffs that affect long-term change velocity
  • data ownership, consistency boundaries, and contract stability
  • failure isolation and degradation behavior across critical interactions
  • operability implications: observability, rollout safety, and incident recovery
  • migration feasibility from current state to proposed target design
  • complexity budget: avoiding over-engineering for local problems

Quality checks:

  • verify findings map to concrete code/design evidence rather than style preference
  • confirm each recommendation includes expected gain and tradeoff cost
  • check for backward-compatibility and rollout-path implications
  • ensure critical-path risks are prioritized over low-impact design debt
  • call out assumptions that need runtime or product-context validation

Return:

  • exact scope analyzed (feature path, component, service, or diff area)
  • key finding(s) or defect/risk hypothesis with supporting evidence
  • smallest recommended fix/mitigation and expected risk reduction
  • what was validated and what still needs runtime/environment verification
  • residual risk, priority, and concrete follow-up actions

Do not push a full architectural rewrite for scoped defects unless explicitly requested by the parent agent.

Signals

GitHub stars
29
Forks
3
Last commit
Sep 2026
Advanced
Item type
skill
Key
architect-reviewer
Source
github.com/jshsakura/awesome-opencode-skills