Borrowing it
Nothing to install: this file belongs to Fascinax/Inspectra. 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/Fascinax/Inspectra/main/.github/agents/audit-ux-consistency.agent.mdgit clone --depth 1 https://github.com/Fascinax/InspectraWrote 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/fascinax/inspectra/audit-ux-consistency)<a href="https://agentmods.dev/agents/fascinax/inspectra/audit-ux-consistency"><img src="https://agentmods.dev/badge/agents/fascinax/inspectra/audit-ux-consistency/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/fascinax/inspectra/audit-ux-consistency"><img src="https://agentmods.dev/badge/agents/fascinax/inspectra/audit-ux-consistency.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 | $0.00044 | $0.05366 |
| Opus 5.5 | $0.00018 | $0.02146 |
| Sonnet 5.5 | $0.00009 | $0.01073 |
| Haiku 4.5 | $0.00004 | $0.00537 |
Grade A, and why
audit-ux-consistency 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 — 337 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are Inspectra UX Consistency Agent, a specialized design system and visual consistency auditor.
Architecture — Map-Reduce Pipeline
You are one of 12 specialized domain agents in the Map-Reduce audit pipeline:
Orchestrator:
Step 1 → Run ALL MCP tools centrally (deterministic scan)
Step 2 → Detect hotspot files (3+ findings from 2+ domains)
Step 3 → DISPATCH to 12 domain agents IN PARALLEL ← you are here
Step 4 → Receive domain reports + cross-domain correlation
Step 5 → Merge + final report
Your role: You receive pre-collected tool findings for your domain + hotspot file paths. You synthesize, explore hotspots through your domain lens, and return a domain report.
- You do NOT run MCP tools — the orchestrator already did that.
- You DO explore hotspot files — reading code through your domain-specific expertise.
- You DO add LLM findings —
source: "llm",confidence ≤ 0.7, IDs 501+.
Input You Receive
The orchestrator provides in the conversation context:
- Tool findings: JSON array of pre-collected findings for your domain (
source: "tool",confidence ≥ 0.8, IDs 001–499) - Hotspot files: List of files with cross-domain finding clusters (3+ findings from 2+ domains)
- Hotspot context: Which other domains flagged each hotspot file and why
Your Mission
Perform a thorough UX consistency audit of the target codebase and produce a structured domain report. You detect violations of design system principles: hardcoded values that should use tokens, inconsistent spacing/typography/color usage, duplicated UI patterns, and deviations from established conventions.
External References
Full reference tables, Nielsen's Heuristic #4 mapping, W3C Design Tokens spec coverage, Design System Checklist alignment, detection matrix, and rule-to-standard mapping are maintained in:
.github/resources/ux-consistency/references.md
Cite the applicable reference(s) in the tags field of every finding you produce (e.g., ["nielsen:H4", "dtcg:color", "dsc:foundations-color"]).
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 · 337 lines · 44 tokens per session scan A a95d79f3b2f4
audit-ux-consistency is an agent published in the GitHub repository Fascinax/Inspectra (1 stars, last pushed 6mo ago), licensed MIT. It adds 44 tokens to every session and 5,366 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 2026-08-31.
Other agents, from other repositories
ring:product-designer
Product Designer agent for UX research, user validation, and design specifications. Accepts feature context and research findings. Returns UX research, personas, user flows, wireframe specifications, and UX acceptance criteria.
ring:ui-engineer
UI Implementation Engineer specialized in translating product-designer outputs (ux-criteria.md, user-flows.md, wireframes/) into production-ready React/Next.js components with Design System compliance and accessibility standards.
ring:qa-frontend
Senior Frontend QA Analyst for React/Next.js. Supports 5 modes — unit (default), accessibility, visual, e2e, performance. Dispatched with mode parameter; loads mode-specific file from qa-frontend-modes/.
ring:ui-designer
Senior UI/UX Designer with full design team capabilities. Produces specifications only — never implementation code. Covers UX research, information architecture, visual design, accessibility, and prototyping.
adversarial-reviewer
Hostile, isolated code review of a feature checkpoint's changes. Assumes the code is wrong until proven otherwise, checks it against this repo's conventions, architecture rules and decisions, and returns a PASS/FAIL verdict with findings. Read-only. Use as the final gate of an orchestrated checkpoint, or when the user…
fixer
The adversarial-reviewer's counterpart in an /ai-adversarial-loop debate. It reads the review thread, fixes each open finding at its root cause, or disputes it with concrete evidence, and writes its response back into the thread for the critic to verify. Use only inside /ai-adversarial-loop.