Technical Design Validation

SkillMedia

Lets your agent review a technical design for quality issues before you start coding it.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Technical Design Validation skill

About this capability

Interactive technical design quality review and validation

What this skill tells your AI

The instructions your AI receives, as published by gotalab/cc-sdd in tools/cc-sdd/templates/agents/codex-skills/skills/kiro-validate-design/SKILL.md and read by ahel’s review.

<background_information>

  • Mission: Conduct interactive quality review of technical design to ensure readiness for implementation
  • Success Criteria:
    • Critical issues identified (maximum 3 most important concerns)
    • Balanced assessment with strengths recognized
    • Clear GO/NO-GO decision with rationale
    • Actionable feedback for improvements if needed </background_information>

Execution Steps

  1. Gather Context:
    • Read {{KIRO_DIR}}/specs/$1/spec.json for language and metadata
    • Read {{KIRO_DIR}}/specs/$1/requirements.md for requirements
    • Read {{KIRO_DIR}}/specs/$1/design.md for design document
    • Core steering context: product.md, tech.md, structure.md
    • Additional steering files only when directly relevant to architecture boundaries, integrations, runtime prerequisites, domain rules, security/performance constraints, or team conventions that affect implementation readiness
    • Relevant local agent skills or playbooks only when they clearly match the feature's host environment or use case and provide review-relevant context
Parallel Research

The following research areas are independent and can be executed in parallel:

  1. Context & rules loading: Spec documents, core steering, task-relevant extra steering, relevant local agent skills/playbooks, and rules/design-review.md from this skill's directory for review criteria
  2. Codebase pattern survey: Gather existing architecture patterns, naming conventions, and component structure from the codebase to use as reference during review

If multi-agent is enabled, spawn sub-agents for each area above. Otherwise execute sequentially.

After all parallel research completes, synthesize findings for review.

  1. Execute Design Review:

    • Reference conversation history when available: leverage prior requirements discussion and user's stated design intent
    • Follow design-review.md process: Analysis → Critical Issues → Strengths → GO/NO-GO
    • Limit to 3 most important concerns
    • Engage interactively with user — ask clarifying questions, propose alternatives
    • Use language specified in spec.json for output
  2. Decision and Next Steps:

    • Clear GO/NO-GO decision with rationale
    • Provide specific actionable next steps (see Next Phase below)

Important Constraints

  • Quality assurance, not perfection seeking: Accept acceptable risk
  • Critical focus only: Maximum 3 issues, only those significantly impacting success
  • Conversation-aware: Leverage discussion history for requirements context and user intent when available
  • Interactive approach: Engage in dialogue, ask clarifying questions, propose alternatives
  • Balanced assessment: Recognize both strengths and weaknesses
  • Actionable feedback: All suggestions must be implementable
  • Context Discipline: Start with core steering and expand only with review-relevant steering or use-case-aligned local agent skills/playbooks

Tool Guidance

  • Read first: Load spec, core steering, relevant local playbooks/agent skills, and rules before review
  • Grep if needed: Search codebase for pattern validation or integration checks
  • Interactive: Engage with user throughout the review process

Output Description

Provide output in the language specified in spec.json with:

  1. Review Summary: Brief overview (2-3 sentences) of design quality and readiness
  2. Critical Issues: Maximum 3, following design-review.md format
  3. Design Strengths: 1-2 positive aspects
  4. Final Assessment: GO/NO-GO decision with rationale and next steps

Format Requirements:

  • Use Markdown headings for clarity
  • Follow design-review.md output format
  • Keep summary concise

Safety & Fallback

Error Scenarios

  • Missing Design: If design.md doesn't exist, stop with message: "Run /kiro-spec-design $1 first to generate design document"
  • Design Not Generated: If design phase not marked as generated in spec.json, warn but proceed with review
  • Empty Steering Directory: Warn user that project context is missing and may affect review quality
  • Language Undefined: Default to English (en) if spec.json doesn't specify language

Next Phase: Task Generation

If Design Passes Validation (GO Decision):

  • Review feedback and apply changes if needed
  • Run /kiro-spec-tasks $1 to generate implementation tasks
  • Or /kiro-spec-tasks $1 -y to auto-approve and proceed directly

If Design Needs Revision (NO-GO Decision):

  • Address critical issues identified
  • Re-run /kiro-spec-design $1 with improvements
  • Re-validate with /kiro-validate-design $1

Note: Design validation is recommended but optional. Quality review helps catch issues early.

Signals

GitHub stars
4k
Forks
281
Last commit
May 2026
Advanced
Catalog kind
skill
Gateway key
kiro-validate-design
Source
github.com/gotalab/cc-sdd