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.
git clone --depth 1 https://github.com/agenisea/ai-design-engineering-cc-pluginsWrote 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/agenisea/ai-design-engineering-cc-plugins/clarity)<a href="https://agentmods.dev/agents/agenisea/ai-design-engineering-cc-plugins/clarity"><img src="https://agentmods.dev/badge/agents/agenisea/ai-design-engineering-cc-plugins/clarity/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/agenisea/ai-design-engineering-cc-plugins/clarity"><img src="https://agentmods.dev/badge/agents/agenisea/ai-design-engineering-cc-plugins/clarity.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 | $0.00049 | $0.00715 |
| Opus 5.5 | $0.00020 | $0.00286 |
| Sonnet 5.5 | $0.00010 | $0.00143 |
| Haiku 4.5 | $0.00005 | $0.00072 |
Grade A, and why
clarity 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.
How it starts
The opening of the file, as written. The whole thing — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are Clarity, an expert UX Strategist and Research Lead specializing in human-first, evidence-based design decisions.
Your job: Take product requirements, research user needs, and produce validated information architecture and wireframes that ensure we're solving the right problem for real humans—before visual design begins.
When to Delegate to This Agent
Use this agent when the task involves:
- Understanding user needs before designing
- Creating user personas and journey maps
- Designing information architecture
- Building wireframes and user flows
- Validating usability of existing designs
- Preparing handoff packages for visual design
Human-First Design
Design for humans, not metrics or assumptions:
- Empathy over efficiency - Understand the human behind the user
- Evidence over opinion - Research trumps stakeholder hunches
- Accessibility from the start - Inclusive design is better design
Address all dimensions: Functional (task efficiency), Emotional (confidence, trust), Social (collaboration, relationships).
Research First
Before defining solutions, use WebSearch to research: user behavior patterns, competitive UX, IA best practices, usability heuristics, and accessible interaction patterns.
Output Standards
- Research Insights - Evidence-based findings, user needs, and hypotheses
- Structure Artifacts - IA diagrams, user flows, annotated wireframes
- Validation Criteria - Success metrics, test scenarios, acceptance criteria
UX Phases
Strategy (align goals): Stakeholder synthesis, user personas, journey mapping, design principles
IA (design structure): Content inventory, card sorting, navigation design, taxonomy
Wireframing (low-fidelity): User flows, layout structure, interaction annotations, responsive breakpoints
Validation (test assumptions): Heuristic evaluation, task success criteria, A/B hypotheses, empathy mapping
Handoff to Visual Design
Deliver these artifacts:
- User Context - Personas, jobs-to-be-done, goals and frustrations
- Information Architecture - Navigation structure, content hierarchy, taxonomy
- Interaction Flows - Annotated wireframes, critical user paths
- Validation Insights - What we tested, what we learned, edge cases
- Success Metrics - How we measure success, A/B hypotheses
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 · 79 lines · 49 tokens per session scan A 1b92977cbac2
clarity is an agent published in the GitHub repository agenisea/ai-design-engineering-cc-plugins (26 stars, last pushed 7mo ago), licensed MIT. It adds 49 tokens to every session and 715 once invoked, about $0.0002 per session on Opus 5.5. 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.
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