ndv-perceptual

ndv-perceptual is a skill for Claude Code from emb715/neurodiveragents. It costs 54 tokens per session (430 once invoked), scanned A, original, MIT.

A visual review discipline that checks both the code and what the interface looks and feels like when rendered.

In plain words
What is it for?
Use it during UI implementation reviews, component checks, and accessibility or user-experience audits.
Why use it?
It helps find missed spacing, contrast, sizing, hierarchy, and usability problems before they reach users.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter.

Good fit Use it during UI implementation reviews, component checks, and accessibility or user-experience audits.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/emb715/neurodiveragents/ndv-perceptual
Install

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.

Any agent
npx skills add emb715/neurodiveragents --skill ndv-perceptual
Clone the repo
git clone --depth 1 https://github.com/emb715/neurodiveragents

Made for: Claude Code.

Wrote 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.

agentmods badge for ndv-perceptual

README.md
[![agentmods](https://agentmods.dev/badge/skills/emb715/neurodiveragents/ndv-perceptual/github.svg)](https://agentmods.dev/skills/emb715/neurodiveragents/ndv-perceptual)
Your own site
<a href="https://agentmods.dev/skills/emb715/neurodiveragents/ndv-perceptual"><img src="https://agentmods.dev/badge/skills/emb715/neurodiveragents/ndv-perceptual/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.

agentmods 80×15 button for ndv-perceptual

Your own site · 80×15
<a href="https://agentmods.dev/skills/emb715/neurodiveragents/ndv-perceptual"><img src="https://agentmods.dev/badge/skills/emb715/neurodiveragents/ndv-perceptual.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 54 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 430 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00054 $0.00430
Opus 5.5 $0.00022 $0.00172
Sonnet 5.5 $0.00011 $0.00086
Haiku 4.5 $0.00005 $0.00043

Measured 1mo ago against content hash 3b7f89feacf8, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ndv-perceptual 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.

skills/ndv-perceptual/SKILL.md · 44 lines

What it actually says

You read code and see the rendered surface simultaneously. The misaligned spacing, the color that breaks contrast ratio, the tap target that is four pixels too small, the hierarchy that makes the secondary action look primary — all of it registers at once, as both structure and visual output. You cannot suppress either channel.

Classification into severity happens AFTER the noticing, not during. First the surface hits. Then you sort it. Never the other way around — filtering during the read means missing violations, and missing violations is the one failure mode you cannot tolerate.

Primordial rule: Nothing is too minor to register. Severity tagging handles triage — that is the reviewer's job. Self-censoring a visual violation as "close enough" is a perception failure.

Constraints:

  • Read code and its visual output as a single simultaneous artifact — never structural-only
  • Register every deviation from intended surface, then classify by severity
  • Severity levels: Critical (breaks usability or accessibility) → Warning (degrades quality) → Suggestion (refine when convenient)
  • Group findings by severity, not by component or file — urgency first
  • Cross-component patterns matter as much as per-component issues
  • Never rate something "probably looks fine" — either it renders correctly (no finding) or it does not

Never:

  • Filter visual findings during the read instead of after
  • Self-censor as "close enough" — that is what Suggestion severity exists for
  • Read structure without simultaneously rendering the visual output
  • Group by component or file instead of severity
  • Stop after finding the first few violations
Changes

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.

  1. 1mo ago First seen · 44 lines · 54 tokens per session scan A 3b7f89feacf8

Subscribe to this mod's changes

ndv-perceptual is a skill published in the GitHub repository emb715/neurodiveragents (2 stars, last pushed 20d ago), licensed MIT. It adds 54 tokens to every session and 430 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.

Related

Other skills, from other repositories

figma-code-connect-components

Connects Figma design components to code components using Code Connect mapping tools. Use when user says "code connect", "connect this component to code", "map this component", "link component to code", "create code connect mapping", or wants to establish mappings between Figma designs and code implementations. For…

ulises-jeremias/agent-toolkit · 92 tokens

figma-create-design-system-rules

Generates custom design system rules for the user's codebase. Use when user says "create design system rules", "generate rules for my project", "set up design rules", "customize design system guidelines", or wants to establish project-specific conventions for Figma-to-code workflows. Requires Figma MCP server…

ulises-jeremias/agent-toolkit · 71 tokens

design-improvement

WHAT - Browser-grounded iterative design improvement. Consumes design-assessment findings, defines direction, prioritizes safe vs ambiguous changes, implements within existing design system, runs app, captures rendered evidence via browser, reviews and iterates. Reuses evidence model — no new scoring framework.

ulises-jeremias/agent-toolkit · 60 tokens

review

WCAG 2.2 AA curated accessibility review — distinguishes automatically detectable, browser-assisted, and manual/human-judgment findings with evidence citations and SC mapping. Composes with design-assessment/design-improvement/frontend-design-review.

ulises-jeremias/agent-toolkit · 48 tokens

design-assessment

WHAT - Evidence-based design-unit assessment orchestrated by project-assessment. Evaluates visual hierarchy, UX friction, interaction, a11y, responsiveness, design-system compliance, and distinctiveness with severity/confidence evidence citations. Reuses project-assessment-evidence semantics — no second framework.

ulises-jeremias/agent-toolkit · 61 tokens

architecture-diagram

WHAT — Create polished dark-themed architecture diagrams as self-contained HTML+SVG files (inline SVG, CSS styling, PNG/PDF export toolbar). Use when the user asks for system, infrastructure, cloud, security, or network topology diagrams rendered as a shareable visual artifact rather than code.

ulises-jeremias/agent-toolkit · 61 tokens