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

Annotations already mark it readOnly, idempotent, and non-destructive. The description adds real behavioral context: API-key authentication, refusal without the key, one-call response behavior, and payload size justification. No contradiction with 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 front-loaded with the core action and every major sentence adds real value. However, it is a long paragraph, and some pricing and response-ceiling detail could be trimmed without losing essential guidance.

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 one-parameter read tool with annotations, an output schema, and a rich description, the definition covers identifier handling, auth requirements, refusal behavior, alternative tools, and response shape. Nothing needed for correct invocation is missing.

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 covers the parameter fully, but the description enriches it further by explaining that id accepts both 'M001' and slug values, matching is case-insensitive, and values should come verbatim from find_academy_modules rows. It even ties the id format to query_knowledge_graph node ids.

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?

States a specific verb and resource: 'Read one Academy training module in full', with the body, objectives, languages, and paid-tier context. It clearly distinguishes this from catalogue/search behaviors and from the get_study resource.

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 says when this tool is usable (subscriber API key, Consultant tier) and what happens otherwise: it refuses and find_academy_modules keeps serving the catalogue. It also contrasts with get_study and ties the id/slug source to find_academy_modules and query_knowledge_graph, giving clear routing guidance.

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