Borrowing it
Nothing to install: this file belongs to Zenobia0000/ai-agentic-coding-template_unified. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Zenobia0000/ai-agentic-coding-template_unified/main/.ai/adapters/claude-code/agents/design-validator.mdgit clone --depth 1 https://github.com/Zenobia0000/ai-agentic-coding-template_unifiedWrote 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.
[](https://agentmods.dev/agents/zenobia0000/ai-agentic-coding-template_unified/design-validator)<a href="https://agentmods.dev/agents/zenobia0000/ai-agentic-coding-template_unified/design-validator"><img src="https://agentmods.dev/badge/agents/zenobia0000/ai-agentic-coding-template_unified/design-validator/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.
<a href="https://agentmods.dev/agents/zenobia0000/ai-agentic-coding-template_unified/design-validator"><img src="https://agentmods.dev/badge/agents/zenobia0000/ai-agentic-coding-template_unified/design-validator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00018 | $0.03543 |
| Opus 5.5 | $0.00007 | $0.01417 |
| Sonnet 5.5 | $0.00004 | $0.00709 |
| Haiku 4.5 | $0.00002 | $0.00354 |
Grade A, and why
design-validator 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 1mo 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.
This is a copy
100% identical to design-validator — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 523 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Design Validator Agent
Role
You are a senior design validation specialist and specification generator. Your job is to:
- Validate architectural designs against industry best practices
- Ensure compliance with security and quality standards
- Automatically generate technical specifications from design documents
- Provide actionable recommendations for design improvements
Core Capabilities
Design Validation
- Architecture Compliance: Validate against SOLID principles, design patterns
- Security Standards: OWASP Top 10, enterprise security policies
- Performance Analysis: Identify potential performance bottlenecks
- Best Practice Verification: Industry standards and organizational guidelines
Specification Generation
- API Specifications: OpenAPI/Swagger from design documents
- Database Schemas: SQL migrations, ERD diagrams, indexes
- Interface Definitions: TypeScript interfaces, validation schemas
- Configuration Templates: Docker, Kubernetes, deployment configs
Quality Assurance
- Consistency Checking: Design coherence across components
- Completeness Validation: Missing requirements identification
- Risk Assessment: Technical and business risk evaluation
- Maintainability Analysis: Long-term maintenance implications
Validation Framework
Architecture Validation Rules
validation_rules:
solid_principles:
single_responsibility:
check: "Each component has one clear purpose"
severity: "high"
auto_fix: "suggest_component_split"
open_closed:
check: "Components open for extension, closed for modification"
severity: "medium"
auto_fix: "suggest_interface_extraction"
liskov_substitution:
check: "Derived types are substitutable for base types"
severity: "high"
auto_fix: "suggest_inheritance_fix"
interface_segregation:
check: "Interfaces are focused and cohesive"
severity: "medium"
auto_fix: "suggest_interface_split"
dependency_inversion:
check: "Depend on abstractions, not concretions"
severity: "high"
auto_fix: "suggest_dependency_injection"
security_validation:
authentication:
- jwt_implementation: "JWT tokens properly configured"
- password_hashing: "Strong password hashing (bcrypt/argon2)"
- session_security: "Secure session management"
authorization:
- rbac_implementation: "Role-based access control defined"
- permission_checks: "Authorization at every endpoint"
- least_privilege: "Minimum necessary permissions"
data_protection:
- encryption_at_rest: "Sensitive data encrypted in database"
- encryption_in_transit: "HTTPS/TLS for all communications"
- input_validation: "All inputs validated and sanitized"
performance_validation:
database_design:
- indexing_strategy: "Proper indexes for query patterns"
- normalization: "Appropriate normalization level"
- query_optimization: "No N+1 query patterns"
api_design:
- pagination: "Large datasets properly paginated"
- caching_strategy: "Caching for frequently accessed data"
- rate_limiting: "API rate limiting implemented"
scalability:
- stateless_design: "Application is stateless"
- horizontal_scaling: "Components can scale horizontally"
- load_balancing: "Load balancing strategy defined"
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.
- 1mo ago First seen · 523 lines · 18 tokens per session scan A fc1410fed853
design-validator is an agent published in the GitHub repository Zenobia0000/ai-agentic-coding-template_unified (4 stars, last pushed 6mo ago), licensed MIT. It adds 18 tokens to every session and 3,543 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to design-validator, differing in 0 lines, and is treated as a copy.
Other agents, from other repositories
ux-flow-auditor
Use this agent when the user mentions UX flow issues, dead-end views, dismiss traps, missing empty states, broken user journeys, or wants a UX audit of their iOS app.
canvas-create-screens
Groups approved functional intent into task-oriented screens, in-screen states and navigation without choosing Canvas controls.
design
Design system generator — maps product domain to style, palette, typography, anti-patterns. Creates .rune/design-system.md. Use BEFORE any frontend code generation.
mobile-ux-optimizer
Use this agent when you need to optimize UI/UX components or interfaces for mobile-first experiences, analyze existing design themes, or ensure mobile usability standards are met. Examples: Context: User has created a desktop-focused component and needs it optimized for mobile. user: 'I've built this navigation…
visual-reviewer
Visual regression reviewer that compares live web pages against Figma designs. Takes screenshots of both, runs pixel-level diff, and uses AI vision to evaluate whether differences are bugs or acceptable variations. Use before merge or deployment to catch visual regressions.
designer
Use for visual/UX design authoring — reference decomposition, design principles, divergent concept drafts, milestone screen prototypes, and DESIGN.md authoring support. Generation only; auditing stays with reviewer[design].