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

The description discloses that schema is injected into the page head and logged, which is useful, but it generalizes this to all supported types, though robots_txt, llms_txt, etc. may not inject into the head. It also omits the 'markdown_file' type listed in the schema and uses inconsistent names ('robots' vs 'robots_txt', 'entity' vs 'entity_schema'), providing partial and potentially misleading behavior.

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 three concise sentences, front-loaded with the main action, and each sentence adds relevant information: purpose, behavioral detail, and supported types. No unnecessary fluff.

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?

The description conveys the core purpose and one behavioral detail, but the tool is complex (4 params, nested object, multiple deployment types) and the schema carries most of the parameter context. The description omits the full type list (markdown_file) and doesn't explain return values, so it is not fully complete despite the rich schema.

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?

Input schema coverage is 100% with detailed descriptions for each parameter. The description adds no additional parameter semantics beyond what the schema already provides, which matches the baseline for high schema coverage.

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 'Deploy JSON-LD schema markup directly to a specific page on your connected WordPress site', using a specific verb (deploy), resource (schema markup/page), and scope. This distinguishes it from siblings like citerank_generate_schema (generation) and citerank_analyze_* (analysis).

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 implies deployment usage, saying it deploys to a WordPress page and supports multiple deployment types, but doesn't explicitly contrast with alternatives or state when not to use it. The context is clear enough for a deployment action, but no exclusions are given.

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