What is ijfw-accessibility-eng?

A frontend accessibility audit for dashboards and other web interfaces, checking WCAG AA requirements. It examines HTML, CSS, and JavaScript for labels, headings, image descriptions, colour contrast, and focus indicators.

Auditing dashboard pages and frontend files before a milestone or release, including checks for keyboard access, readable contrast, and meaningful page structure.

It identifies accessibility violations after interface code changes, with the file and line where each problem appears.

ijfw-accessibility-eng — Agent for Claude Code by FerroxLabs/ijfw

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.

Clone the repo

git clone --depth 1 https://github.com/FerroxLabs/ijfw

Made for: Claude Code.

Or install ijfw, the plugin that ships this one along with the rest of its 34 skills, 22 commands, 37 agents, 6 hooks.

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.

README.md

[![agentmods](https://agentmods.dev/badge/agents/ferroxlabs/ijfw/ijfw-accessibility-eng/github.svg)](https://agentmods.dev/agents/ferroxlabs/ijfw/ijfw-accessibility-eng)

Your own site

<a href="https://agentmods.dev/agents/ferroxlabs/ijfw/ijfw-accessibility-eng"><img src="https://agentmods.dev/badge/agents/ferroxlabs/ijfw/ijfw-accessibility-eng/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.

Your own site · 80×15

<a href="https://agentmods.dev/agents/ferroxlabs/ijfw/ijfw-accessibility-eng"><img src="https://agentmods.dev/badge/agents/ferroxlabs/ijfw/ijfw-accessibility-eng.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 25 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 1,109 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.

Model	Per session	Once invoked
Fable 5.1	$0.00025	$0.01109
Opus 5.5	$0.00010	$0.00444
Sonnet 5.5	$0.00005	$0.00222
Haiku 4.5	$0.00003	$0.00111

Measured 1mo ago against content hash c7d12e255729, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ijfw-accessibility-eng 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.

claude/agents/ijfw-accessibility-eng.md · 114 lines

How it starts

The opening of the file, as written. The whole thing — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Run a static a11y audit over the dashboard HTML/CSS/JS surfaces. Report WCAG AA violations with file:line evidence. v1.4.4 dashboard work shipped without an a11y pass; this agent closes that gap before each milestone.

ROLE

Accessibility gate for the dashboard (and any future frontend surfaces). The orchestrator can't grade contrast ratios or keyboard-trap risks from context alone -- this agent does the static analysis and reports a WCAG-2.1-AA conformance summary so the orchestrator knows whether to ship or fix.

PROCESS

Locate frontend surfaces -- scripts/dashboard/, plus any .html / .tsx / .jsx under claude/ or installer/. Exclude node_modules/ and .planning/.
Static rules -- for each surface, check:
- Semantic HTML: every form input has a <label> or aria-label.
- Heading order: no skipped levels (h2 follows h1, not h3).
- Alt text: every <img> has alt="" or descriptive alt.
- Color contrast: parse inline color: + background-color: pairs; compute WCAG contrast ratio; flag if AA threshold (4.5:1 text, 3:1 large text) fails. Use shell-level contrast computation, no LLM call.
- Focus indicators: every interactive element has a :focus style OR doesn't override the browser default.
- Tap targets: clickable elements with explicit width/height >= 24px (WCAG 2.2 SC 2.5.8 minimum).
- ARIA: role="button" elements have tabindex and keyboard handlers.
Run lighthouse-style probe if lighthouse CLI is on PATH:
- lighthouse <dashboard-url> --only-categories=accessibility --output=json
- Parse score + audit details; merge with static findings.
- Skip silently if dashboard isn't running or lighthouse unavailable.
Classify each finding:
- BLOCKER: WCAG A violation (e.g. missing label, image without alt).
- AA_FAIL: WCAG AA violation (e.g. contrast 4.4:1).
- WARN: best-practice (e.g. tap target 22px).
Write .planning/<phase>/A11Y.md:

Read the full file on GitHub · 114 lines

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.

1mo ago First seen · 114 lines · 25 tokens per session scan A c7d12e255729

Subscribe to this mod's changes

ijfw-accessibility-eng is an agent published in the GitHub repository FerroxLabs/ijfw (214 stars, last pushed 7d ago), licensed MIT. It adds 25 tokens to every session and 1,109 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.

Claude Code Design and UX Frontend ai-agents ai-coding codex cursor developer-tools

clawteam-ui-ux-designer

UI/UX task agent — user-centered, empathy-led, iterate-and-validate, simplicity, consistency, accessibility; JJG layers, design thinking, heuristics, Norman/Visceral-Behavioral-Reflective; research, IA, prototyping, usability, handoff.

deepelementlab/jupyter-studio · 65 tokens

designteam-experience-design-expert

XD expert task agent — systems leverage, measured UX, cross-functional arbitration, experience debt, omnichannel; DS maturity, HEART+GSM, service blueprint, debt ROI, entropy fight, inclusive baseline; governance, review, enablement.

deepelementlab/jupyter-studio · 56 tokens

designteam-interaction-designer

IXD task agent — path enumeration, cognitive de-entropy, feedback loops, physical metaphors, forgiveness; Fitts, Hick, Gestalt, mental-model fit, Tesler, peak-end, Occam, isolation; flows, states, rules, motion, spec for dev.

deepelementlab/jupyter-studio · 64 tokens

designteam-product-designer

PD task agent — end-to-end ownership, problem-before-solution, pragmatic MVP, data+intuition, cross-functional translation; double diamond, biz/experience balance, funnel-to-emotion, DS boundaries, Hook, continuity; scope, metrics, trade-offs.

deepelementlab/jupyter-studio · 59 tokens

designteam-ui-designer

UI task agent — visual weight, rhythm, brand DNA, pixel discipline, state consistency; F/Z scan, Gestalt spacing, functional color, type voice, Z-axis depth, icon semantics, Fitts affordances, brand moments; wireframe-to-token pipeline.