Ask Agent Ready in natural language

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

Annotations already declare readOnlyHint, destructiveHint, idempotentHint, openWorldHint. The description adds valuable behavioral context: returns Schema.org-typed results, optional itemType narrows corpus, mode 'summarize' adds extractive summary. No contradictions.

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?

Two sentences efficiently convey purpose, access, return type, and optional parameters. No extraneous words; each sentence earns its place.

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?

Given the tool's complexity (3 params, output schema exists, rich annotations), the description covers essential aspects: purpose, access, parameters, and return type. It could mention that results are paginated or include an example, but output schema covers return structure adequately.

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?

Schema coverage is 100%, so baseline is 3. The description adds meaning beyond schema by explaining 'Natural-language search' for q, 'narrows to one corpus type' for itemType, and 'adds extractive summary' for mode. This provides functional context beyond parameter names and basic descriptions.

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 'Natural-language search over Agent Ready's own content', specifying the verb and resource. It distinguishes from siblings like get_scan and scan_site by focusing on content search rather than scanning or validation.

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 explicitly notes 'Public, no API key required' and explains optional filters. While it doesn't explicitly contrast with siblings, the context makes usage clear. A brief when-not-to-use statement would elevate to 5.

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