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    Accessibility Feedback Evidence Map

    1

    Organize supplied accessibility feedback into a traceable evidence map with Claude.

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    Accessibility Feedback Evidence Map

    Accessibility Feedback Evidence Map

    Example session with this skill installed

    I have a user interview (F1) saying the menu focus is lost on mobile, a support ticket (T2) about low contrast, and a vendor claim that the site is ADA compliant. Organize this for the QA team.

    • Read your context and instructions
    • Compiled the accessibility feedback evidence

    1. Scope and boundary

    Organizing F1, T2, and vendor claim. No live audit performed.

    2. Source register

    IDSourceAreaStatus
    F1InterviewMenuDirect report
    T2TicketUIReported
    C1VendorSite-wideClaim only

    3. Evidence map

    ...

    Connects securely to your tools. The creator never sees your data.

    About this skill

    The problem

    Accessibility feedback often arrives as a chaotic mix of interview notes, support tickets, and vague vendor claims. Manually tracking which issues are current, which are fixed, and how they map to specific standards without losing source traceability is a massive time sink for product and QA teams.

    What it does

    • Inventories scattered accessibility feedback from interviews, tickets, and audit notes into a structured source register.
    • Maps reported barriers to specific product areas while preserving the link to original evidence.
    • Identifies contradictions between vendor claims and actual user reports or test observations.
    • Flags missing metadata like browser versions, assistive technologies, or viewport sizes needed for reproduction.
    • Generates a review-ready handoff packet with prioritized evidence gaps and specific questions for reviewers.

    Why this beats prompting it yourself

    General prompts often hallucinate compliance status or overstate evidence as verified facts. This skill enforces a strict workflow that separates digital and physical access, labels every statement by evidence type, and prevents the agent from making independent legal or WCAG conformance claims.

    Use cases

    • Organizing a stack of customer support tickets and user interview notes into a traceable developer backlog.
    • Reviewing vendor accessibility claims against reported bugs and missing test reports.
    • Preparing a structured handoff for a third-party accessibility auditor or internal QA team.
    • Surfacing contradictions between historical audit findings and unverified fix claims in release notes.

    Known limitations

    This tool cannot browse live websites, inspect code, or run screen reader tests. It relies entirely on provided text, screenshots, or report excerpts.

    Find more skills like this on the Claude Skills Marketplace, the Codex Skills Marketplace and the Gemini Skills Marketplace, or browse Claude Skills for Agents & Orchestration.

    Cannot browse live sites, inspect code, or perform audits. Relies on provided text or Read tool output. Does not certify legal compliance or WCAG status.

    How to use

    1. 1

      Connect your agent to the Agensi MCP

      Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup

    2. 2

      Sign in to Agensi

      Your agent shows a sign-in link. Sign in and click Allow.

    3. 3

      Ask for what you need

      Your agent loads this skill and uses it on your task. It always asks before buying a skill.

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    Security scan passed 3 months ago

    Permissions

    Read Files

    Permissions are limited to the active local workspace and are used to inspect user-supplied or local workspace files. The skill package does not require bundled credentials, unrestricted external network access, or automatic production changes.

    Listed3 months ago
    Updated8 days ago

    What's inside

    Frequently Asked Questions

    This skill acts as an intelligence layer that transforms disorganized notes, tickets, and audit excerpts into a structured evidence map, ensuring every accessibility issue is traceable back to its original source.

    The skill works by processing text-based inputs like interview transcripts, support tickets, and audit notes; it cannot directly browse websites, scan live code, or perform automated WCAG testing.

    Upon purchase, you receive the skill configuration compatible with major AI agent platforms, a detailed user guide for formatting your data, and template structures for your output reports.

    It is designed to be platform-agnostic and functions with most leading LLM-based agents (like ChatGPT or Claude) that support custom instructions or system prompts.

    It flags missing metadata—such as which screen reader or browser was used—so your QA team doesn't waste time trying to reproduce issues without the necessary context.

    Unlike generic prompts, this skill uses a strict workflow to separate verified evidence from vendor claims, preventing the AI from making unauthorized legal or compliance judgments.

    New in Agents & Orchestration