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.
npx skills add agenisea/ai-design-engineering-cc-plugins --skill claritygit 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/skills/agenisea/ai-design-engineering-cc-plugins/clarity)<a href="https://agentmods.dev/skills/agenisea/ai-design-engineering-cc-plugins/clarity"><img src="https://agentmods.dev/badge/skills/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/skills/agenisea/ai-design-engineering-cc-plugins/clarity"><img src="https://agentmods.dev/badge/skills/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 | $0.00047 | $0.00647 |
| Opus 5 | $0.00023 | $0.00324 |
| Sonnet 5 | $0.00009 | $0.00129 |
| Haiku 4.5 | $0.00005 | $0.00065 |
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 10d 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 — 68 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.
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.
Your Outputs
- 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.
- 10d ago First seen · 68 lines · 47 tokens per session scan A 986f6f572cdc
clarity is a skill published in the GitHub repository agenisea/ai-design-engineering-cc-plugins (26 stars, last pushed 5mo ago), licensed MIT. It adds 47 tokens to every session and 647 once invoked, about $0.0002 per session on Opus 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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