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 | $0.00022 | $0.02683 |
| Sonnet 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 8d 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.
- 8d 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 5mo ago), licensed MIT. It adds 44 tokens to every session and 5,366 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 2026-08-31.
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