ai-accessibility

ai-accessibility Accessibility Experience Diagnostic Assistant

Overview

The accessibility experience diagnostic assistant is used to answer "Is this page easy to use?", content production, copy optimization, and release preparation. It is suitable for content creators, marketing, operations, and content media to invoke after clarifying business goals, content materials, or analysis targets. It will combine inputs such as visual brief or screenshot descriptions, pasted visual briefs, screenshot descriptions, brand guidelines, page issues, platform specifications, or modifications... to organize key context and output issue attribution, service improvement suggestions, SOPs, or FAQ lists, making it easy to continue execution, review, or delivery. Capability positioning supplement: skills.sh all-time/trending/hot signals show that accessibility has user demand; the platform displays it as a local_service_ops business assistant directory, outputting reviewable diagnostics, suggestions, or production preparation packages.

When to Use

Applicable Scenarios

Users ask questions like "Is this page easy to use?" and need to quickly break down goals, determine priorities, and form actionable results
Content creators, marketing, operations, and content media need to generate issue attribution, service improvement suggestions, SOPs, or FAQ lists around the accessibility experience diagnostic assistant
The user has already prepared the review target (explain the layout, readability, brand consistency, conversion goals, or delivery standards to be checked.), usage scenario (explain the platform, audience, device, campaign, or review scenario the visual materials are intended for.), page or material link (fill in publicly accessible pages, materials, design draft previews, or reference links; for restricted content, please upload instead.), and hopes to organize it into actionable analysis or optimization results
The user needs to turn materials related to the accessibility experience diagnostic assistant into clear conclusions, priorities, and next steps

How to Invoke

Call the AI Skills API directly through the exported Python runner:

Command Example

Basic Invocation

python3 scripts/run.py --params '{}'

Invocation with Common Parameters

python3 scripts/run.py --params '{"goal":"审查目标"}'

Parameter Description

Parameter	Type	Required	Default	Description
`goal`	string	No	-	Explain the layout, readability, brand consistency, conversion goals, or delivery standards to be checked
`audience`	string	No	-	Explain the platform, audience, device, campaign, or review scenario the visual materials are intended for
`materialUrl`	string	No	-	Fill in publicly accessible pages, materials, design draft previews, or reference links; for restricted content, please upload instead; a complete accessible URL is required
`materialFile`	string	No	-	Upload screenshots, images, presentation decks, brand guidelines, product images, or visual reference files
`materialText`	string	No	-	Paste visual briefs, screenshot descriptions, brand guidelines, page issues, platform specifications, or modification goals
`brandRequirements`	string	No	-	Supplement brand guidelines, size ratios, platform restrictions, unchangeable elements, accessibility requirements, or manual review priorities

For the complete machine-readable parameter structure, see references/form-schema.json。

Parameter Value Reference

The current skill has no category parameters that require additional lookup.

Supported input formats

The current skill directly accepts JSON parameters; if the parameters include a link field, please pass a complete, accessible URL.

Example request

The example parameters below can be passed directly to scripts/run.py, and the runner will send them to the AI Skills API.

python3 scripts/run.py --params '{"goal":"审查目标"}'

Equivalent --params JSON：

{
  "goal": "审查目标"
}

Example return result

{
  "success": true,
  "data": {
    "message": "示例结果请以技能真实返回结构为准。"
  },
  "meta": {
    "executionTime": 842,
    "cached": false
  }
}

Deliverables

Problem attribution, service improvement suggestions, SOP or FAQ checklist: organize the core results around the user's goals that can be directly read, reviewed, or delivered.
Interpretation of input materials: combine the review goals (explain the layout, readability, brand consistency, conversion goals, or delivery standards to be checked.), usage scenario (explain the platform, audience, device, campaign, or review scenario the visual materials are intended for.), page or material links (fill in publicly accessible pages, materials, design draft previews, or reference links; for restricted content, please upload instead.) to extract key context and judgment basis.
Next steps: provide priorities, execution suggestions, or a content framework that can be further processed.

Suggestions for using the results

First determine whether the output answers the user's core question about the "Accessibility Experience Diagnostic Assistant."
Then check whether the results cover problem attribution, service improvement suggestions, SOP or FAQ checklist, and whether clear next steps are provided.
If there is little input material, it is recommended to have the user supplement the goals, audience, constraints, or original materials before running.

Preparation before running

AISKILLS_BASE_URL: default https://ai-skills.ai
AISKILLS_API_KEY: required, used for authenticated calls
AISKILLS_TENANT_ID: default default