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analyze_accessibility_evidence

Audit web pages for accessibility by rendering URLs or HTML and running multi-engine checks, preserving evidence for human review before fixes.

Instructions

Render a URL or HTML document, run axe-core plus AccessLens semantic checks (and QualWeb ACT Rules for URL scans), preserve raw per-engine provenance, and persist a pending-human-review report. Do not modify code: present get_review_report to the human first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
session_idNo
url_or_htmlYesA public http(s) URL, or an HTML document.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the side effect of persisting a pending-human-review report, the non-code-modifying guardrail, and the preservation of raw per-engine provenance. It does not mention auth or rate limits, but the core behavioral traits are clearly covered.

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?

Two sentences with no filler; the first sentence front-loads the diagnostic pipeline and the second adds a necessary workflow guard. The first sentence is somewhat dense but every clause earns its place, so just short of top score.

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

Completeness3/5

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

For a complex multi-engine tool with no output schema, it covers the workflow and next step (get_review_report), but fails to explain the role of session_id or what the function returns after persisting the report, leaving notable invocation ambiguity.

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

Parameters2/5

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

Schema coverage is 50%, with session_id lacking any schema description. The tool description likewise omits session_id, only reinforcing url_or_html (already described in schema) and adding the URL-only QualWeb nuance. This leaves one of two parameters semantically opaque.

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?

States a specific pipeline: render a URL/HTML document, run axe-core plus AccessLens semantic checks, QualWeb ACT Rules for URL scans, preserve per-engine provenance, and persist a pending-human-review report. This clearly distinguishes it from sibling review tools by its evidence-preservation and human-review workflow.

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

Usage Guidelines3/5

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

Implies a workflow by instructing the agent to present get_review_report to the human first and not modify code, but never explicitly states when to choose this tool over run_accessibility_review or crawl_accessibility_review, nor any exclusions or alternative conditions.

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