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

No annotations are provided, but the description states 'Read-only. No LLM calls.' which discloses behavior. It also details what each related term includes, giving transparency about the response structure.

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 two sentences, front-loaded with the main purpose. The list of returned fields and usage note earn their place; no redundant text.

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 single-parameter read-only tool, the description covers purpose, usage, output structure, and alternatives. Without an output schema, it adequately describes the return shape.

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 schema already provides 100% coverage of the 'term' parameter description, so the description doesn't need to elaborate. It adds context by explaining the returned graph includes related terms, but the parameter itself is already well-documented.

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 opens with 'Returns the full relationship graph for a given Lexicon term,' clearly stating the verb and resource. It distinguishes from sibling lookup_term by noting that tool is for definitions, while this is for connections.

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: 'Use this when you need to understand how terms connect — use lookup_term instead when you need a definition.' This provides both use case and alternative.

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