Validate JSON-LD structured data

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

Annotations already declare readOnlyHint true, destructiveHint false, and idempotentHint true. The description adds valuable context: it is public, requires no API key, and lists the specific checks performed (freshness, honesty, coherence, etc.), which goes beyond the annotations.

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 concise (two sentences) and front-loaded with the main action. Every sentence earns its place: the first explains what the tool does and the checks, the second clarifies the parameters and unique value.

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 output schema exists, the description need not explain return values. It covers the tool's purpose, input modes, behavioral traits, and unique differentiation, making it complete for an agent to decide and invoke correctly.

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%, and the description adds meaning to each parameter: 'url' is for fetching and validating, 'jsonld' is for validating a string with no network. This adds value beyond the schema 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 specifies a verb (validates), a resource (JSON-LD structured data), and a clear scope (Agent Ready's specific checks: schema lint + agent-coherence). It distinguishes itself from first-party validators, making the purpose unique and unmistakable.

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 states the two usage modes (url or jsonld) and the constraint 'provide exactly one'. It also notes that no API key is required and it's public. While it does not explicitly compare to sibling tools, the siblings appear unrelated, so no further guidance is necessary.

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