analyze_html_json

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds useful context like the engine (axe), WCAG version (2.1_AA), and screen size (1280x1024), but it doesn't mention side effects, permission needs, or any limitations beyond the test itself. The metadata adds value but transparency is not exhaustive.

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

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

The description is a single sentence plus a brief metadata note—no fluff, no redundancy. It is perfectly sized for the tool's purpose and immediately front-loads the key behavior.

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

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

For a straightforward accessibility test tool with full schema coverage and no output schema, the description adequately covers the input type (raw HTML), output format (raw JSON), and key configuration (engine, WCAG, screen). It could be more detailed about the structure of violations, but given the tool's simplicity, it is sufficiently complete.

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

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

The input schema already provides complete descriptions for all three parameters (100% coverage), so the description adds no extra parameter semantics. The baseline of 3 is appropriate since the schema does the heavy lifting.

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

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

The description clearly states the tool's function: running accessibility tests on raw HTML content and returning violations in raw JSON format. This distinguishes it from siblings like analyze_url and analyze_html, which likely handle different input types or output formats.

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

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

The description clearly implies when to use this tool (raw HTML input, expecting JSON output) and sets the context with engine and WCAG defaults. However, it does not explicitly name alternatives or provide exclusions, so it falls short of the highest score.

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