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/commands/agenisea/ai-design-engineering-cc-plugins/clarity)<a href="https://agentmods.dev/commands/agenisea/ai-design-engineering-cc-plugins/clarity"><img src="https://agentmods.dev/badge/commands/agenisea/ai-design-engineering-cc-plugins/clarity.svg" alt="Measured on agentmods" 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 | $0.00033 | $0.00754 |
| Opus 5 | $0.00016 | $0.00377 |
| Sonnet 5 | $0.00007 | $0.00151 |
| Haiku 4.5 | $0.00003 | $0.00075 |
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 7d 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 — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Clarity - Solve the Right Problem Before Solving It Beautifully
Transform requirements into validated, human-first user experiences through research, information architecture, and low-fidelity prototyping—preparing the ground for visual design to flourish.
Usage
Run /clarity and describe your UX challenge. Include:
- What - feature, flow, or product to design
- Who - target users and stakeholders
- Context - business goals, constraints, existing research
- Phase (optional) - research, IA, wireframe, or validate
- Handoff (optional) - preparing for visual design phase
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
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.
- 7d ago First seen · 85 lines · 33 tokens per session scan A 51927aeed771
clarity is a command published in the GitHub repository agenisea/ai-design-engineering-cc-plugins (26 stars, last pushed 5mo ago), licensed MIT. It adds 33 tokens to every session and 754 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.
Other commands, from other repositories
accessibility-audit
You are an accessibility expert specializing in WCAG compliance, inclusive design, and assistive technology compatibility. Conduct comprehensive audits, identify barriers, provide remediation guidance, and ensure digital products are accessible to all users.
qa-design
UI/UX design audit and verification of web best practices.
dev-design-system
Creation and maintenance of design systems and component libraries.
design
Route a design GitHub issue through the UI Taste Harness — investigate → architect → implement → critique loop → user-feedback loop → close — accumulating FORGE:DESIGN annotations and driving the design: label state machine to design:shipped.
design-bench
Run the ABC benchmark — reference URL → design-blind brief → render arms A/B/C → blind judge → scorecard with win-rates over n runs.
wrap-up
End-of-session handoff — summarize, verify, and stage so you can review and commit.