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webability

by io.github.snayyar00
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Start a full accessibility audit

start_audit

Kick off a FULL accessibility audit deliverable for a URL — a persistent, timestamped artifact, not an inline scan. Runs the server-side pipeline (axe + advanced checks + mobile viewports + annotated screenshots + optional agent spot-check) and produces a downloadable report and a formatted Excel workbook (Cover / Status / Barriers / ADA context sheets) stored durably. Returns immediately with an audit id; poll get_audit for progress and, when complete, download URLs. Use this when someone needs a durable artifact to attach as evidence of testing effort for a compliance officer or legal response — for iterating on code, use scan_page + verify_fix instead. Free for everyone; needs a free WebAbility account (sign in when your client prompts you, or run webability login). Set includeAgent:true to add the slower agentic manual-audit pass. To audit a local dev server, open a tunnel (webability-tunnel --port 3000) and pass its URL as url with the printed secret as tunnel_secret; keep the tunnel open until get_audit reports complete (about 5 minutes) — the pipeline loads the page several times.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesURL to audit (a public/staging URL the server can reach, or a webability-tunnel URL — not localhost)
contextYesExplain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
llm_modelYesThe exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess.
includeAgentNoAlso run the agentic manual-audit pass (keyboard/focus/modal exploration). Slower. Default false.
tunnel_secretNoSecret printed by `webability-tunnel`. Required when `url` is a tunnel URL; the URL alone will be refused by the relay. Ignored otherwise.
conversation_idNoEcho the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the annotations (which only flag non-readonly/open-world), it discloses the async contract (returns immediately with an `id`, poll get_audit), the ~5-minute runtime, the need to keep a tunnel open, auth requirements, and the cost of includeAgent. This is genuinely rich behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The critical routing information is front-loaded and the workflow steps follow logically, with no filler sentences. It is on the long side and packs several concerns (auth, tunnel, agent pass) into one paragraph, but each sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex asynchronous, multi-file tool with no output schema, the description supplies everything an agent needs: the immediate return value, how to poll for progress, where results live, and the tunnel/environment constraints. Nothing essential is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the schema already documents each parameter; the description nonetheless adds integration meaning beyond it, explaining when includeAgent should be set and how tunnel_secret pairs with a tunnel URL. It stops short of documenting context/llm_model/conversation_id, which is acceptable since the schema carries them.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Opens with a specific verb and resource ('Kick off a FULL accessibility audit deliverable for a URL') and immediately distinguishes the artifact from an inline scan. It further differentiates from scan_page + verify_fix, so an agent can place it against siblings without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit when-to-use (durable evidence for a compliance officer or legal response) and an explicit when-not (iterating on code -> scan_page + verify_fix). It also covers the local-dev-server case with the tunnel workflow and the precondition of a WebAbility account.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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