Extract named entities and sameAs links

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

Annotations already declare the tool as read-only and non-destructive. The description adds valuable nuance: network behavior differs between 'url' (one HTTP GET) and 'text' (zero network), two execution paths (sampling vs regex fallback) are explained, and the output includes a 'mode' field to indicate which path ran. Dependencies for headless rendering are also noted.

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 front-loaded with the primary purpose and is well-structured into logical sections (overview, paths, when to use). It is longer than ideal but every sentence adds distinct value. Minor redundancy: 'Extract named entities, linked concepts, and sameAs graph nodes' is slightly verbose but acceptable.

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 has an output schema (so return values are documented elsewhere) and 4 well-described parameters, the description covers all essential aspects: input conditions, execution modes, dependencies, and use cases. It is complete for an agent to select and invoke the tool 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%, so baseline is 3. The description adds context beyond the schema: it clarifies the mutual exclusivity of 'url' and 'text' (schema does not mark them required but description explains they are conditionally required), explains the render modes and their implications, and notes that 'respect_robots' is ignored when 'text' is used.

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 begins with a specific verb ('Extract') and resource ('named entities, linked concepts, and sameAs graph nodes'), immediately clarifying the tool's core function. It differentiates from sibling 'audit_schema' by stating that tool is for validating JSON-LD itself, not extracting entities.

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?

Explicitly states 'When to use: building an entity map... or auditing whether a page's entities match its target topic.' It also provides an alternative ('To validate the JSON-LD itself, use audit_schema') and clarifies that either 'url' or 'text' must be provided.

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