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dallask

Accessibility MCP Server

by dallask

export_to_json

Export accessibility audit results to structured JSON, with optional pretty-printing and raw result inclusion. If a URL is provided, an audit runs first.

Instructions

Export audit results as structured JSON. Supports pretty-printing and optional raw results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
prettyNoPretty-print JSON (default: true).
resultsYesAudit results object or URL string. If URL is provided, an audit will be run first.
includeRawNoInclude raw accessibility engine results (default: false).
Behavior2/5

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

With no annotations provided, the description must fully disclose behavioral traits. It fails to mention that providing a URL string will run an audit first, which is a significant side-effect. The description only covers output formatting options (pretty, raw) and does not disclose any potential side effects or state changes. This is a notable transparency gap.

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

Conciseness5/5

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

The description is highly concise, consisting of two short sentences that get straight to the point. It front-loads the core function and mentions the key options without wasting words. Every sentence contributes meaningful information, making it appropriately sized for the tool's simplicity.

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

Completeness2/5

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

Despite the schema detailing parameters, the description omits the crucial context that the 'results' parameter can be a URL which triggers an audit. This dual-mode behavior is not reflected in the description, leaving the tool's full capability ambiguous. With no output schema and no annotations, the description does not sufficiently situate the tool among its siblings or clarify when to use it.

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

Parameters3/5

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

The schema description coverage is 100%, with each parameter already having clear descriptions. The tool description adds minimal semantic value beyond the schema, only loosely referencing 'pretty-printing' and 'optional raw results,' which map to the schema's existing parameter descriptions. Since the schema already explains the parameters well, the description's contribution is marginal.

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?

The description clearly states the tool's function: 'Export audit results as structured JSON.' This is a specific verb+resource that distinguishes it from sibling export tools like export_to_csv and export_to_html_report. It also mentions the supported features (pretty-printing and optional raw results), further clarifying its purpose.

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?

The description implies usage when JSON output of audit results is needed, but provides no explicit guidance on when to choose this tool over alternatives. There is no mention of the fact that passing a URL triggers an audit, which is a critical usage nuance. The context of being a JSON export tool gives some implied direction, but no explicit when/when-not/alternatives are stated.

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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