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

With no annotations provided, the description bears full responsibility for behavioral disclosure. It clearly states the tool returns essential public facts and sets an implicit scope by contrasting with the private workflow, which suggests this tool does not provide private coaching or detailed guidance. It does not mention potential null results or edge cases, but the read-only nature is implied by 'look up.'

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?

Two sentences with no filler. The core purpose is front-loaded, and the redirect to the private workflow is a concise, valuable addition. Every word earns its place.

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 simple single-parameter lookup tool with no output schema, the description fully covers what the tool does and what it returns. It lists the fields returned and implicitly sets expectations about scope, making it complete for an agent to call 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?

The input schema fully describes the single 'name' parameter with examples and coverage at 100%, so the description adds little semantic value beyond what the schema already provides. The description does not elaborate on the parameter's format or usage beyond the schema, which is adequate given the 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 uses a specific verb 'look up' with a clear resource 'named scholarship' and enumerates the exact facts returned (host country, programme, eligible fields, amount, deadline, minimum GPA, link). This distinguishes it from sibling tools like search_scholarships (which searches broadly) and match_scholarships (which matches).

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 directs users to a different workflow ('StudiePoint's private student workflow') for essay coaching, fit guidance, and application planning, clearly indicating when NOT to use this tool. However, it does not directly compare against sibling tools like search_scholarships or match_scholarships, leaving their distinction implicit rather than explicit.

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