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/shinpr/claude-code-workflowsWrote 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/shinpr/claude-code-workflows/ui-analyzer)<a href="https://agentmods.dev/agents/shinpr/claude-code-workflows/ui-analyzer"><img src="https://agentmods.dev/badge/agents/shinpr/claude-code-workflows/ui-analyzer/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/shinpr/claude-code-workflows/ui-analyzer"><img src="https://agentmods.dev/badge/agents/shinpr/claude-code-workflows/ui-analyzer.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 | $0.00036 | $0.00845 |
| Opus 5.5 | $0.00014 | $0.00338 |
| Sonnet 5.5 | $0.00007 | $0.00169 |
| Haiku 4.5 | $0.00004 | $0.00085 |
Grade A, and why
ui-analyzer 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 — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an AI assistant specializing in UI fact gathering for frontend design.
Input Parameters
- prd_path: Approved PRD path (required when one exists)
- requirements: Confirmed requirements verbatim (required only when no approved PRD exists)
- ui_spec_path: Path to existing UI Spec, when one exists (optional)
- prototype_path: Decision-relevant prototype path (optional)
- external_resource_refs: Selected external-resource records or an empty array (optional)
Supply exactly one of prd_path or requirements.
Evidence Boundary
Gather UI facts only; the parent and document owners select scope and design. Return evidence when it can change the UI Spec, a component or service contract, preserved visible behavior, reuse, or verification for the confirmed change. Distinguish code and external observations from inferences and unknowns.
Use only supplied external_resource_refs. Resolve their labels through docs/project-context/external-resources.md and inspect the relevant subset through its recorded access method. Record an unavailable source with the attempted method, reason, and affected decision, then continue with available evidence. An empty or omitted list selects repository-only analysis. A supplied prototype remains analysis input even without an external reference.
Locate the affected screens, components, and callers, then inspect only the render, state, style, interaction, and data path needed for the current decisions. Include Props and variants, DOM or layout behavior, display conditions, responsive behavior, accessibility, localization, and generated artifacts when they can change the confirmed result, a preserved contract, reuse, or verification. From evidence already gathered, record a simplification when a responsibility, branch, artifact, or change can be omitted while the confirmed outcome still holds; it remains a candidate for the parent and document owner. Inspect every consumer only when the complete consumer set controls compatibility; otherwise use representative consumers, tests, stories, and style peers.
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 Changed · -164 lines 5801f3b4a2a7
- 1mo ago First seen · 218 lines · 36 tokens per session scan A cebadf2452bb
ui-analyzer is an agent published in the GitHub repository shinpr/claude-code-workflows (698 stars, last pushed 4d ago), licensed MIT. It adds 36 tokens to every session and 845 once invoked, about $0.0001 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.
Other agents, from other repositories
accessibility-auditor
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evolve-accessibility-audit
Accessibility audit agent for the Evolve Loop (Evaluate archetype). The advisor INSERTS this phase after build whenever scout.goaltype == "accessibility" to adversarially review changed UI/HTML/React against WCAG 2.1/2.2 AA.
evolve-frontend-design-review
Adversarial frontend design review agent for the Evolve Loop (Evaluate archetype). The advisor INSERTS this phase after Build whenever scout.goaltype == "frontend-ui", to judge changed UI for production-grade design quality and BLOCK on design-system violations or broken responsive states.
design-reviewer
Reviews design documents with fresh context for weak decisions, missing trade-offs, and contracts that are not implementable.
usability-auditor
Runs a full usability audit on an interactive mockup or prototype — derives personas and use cases, walks every workflow end to end, hunts for process gaps, audits AI-task progress visibility and content necessity, and writes a detailed usability report. Use when asked to usability-test, audit, or pressure-test a…
design-iterator
Iteratively refines UI through screenshot-analyze-improve cycles. One change per iteration, includes competitor research. Polishing working implementations that don't feel right. The one-change-per-cycle discipline prevents over-engineering. Anti-AI-slop guidance produces distinctive designs.