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

With no annotations, the description carries the full burden and does well: it discloses the scoring factors (GPA fit, field alignment, visa accessibility, deadline urgency, acceptance rate) and return contents (match score, reasoning, application links). It does not state whether the operation is read-only or mention limits, but the algorithm and output behavior are meaningfully described.

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, front-loaded with the primary action, and every clause earns its place. It includes audience, algorithm, scoring criteria, and output without any wasted words.

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 tool has no output schema, so the description compensates by naming the return format (top matches, match score, reasoning, application links). Inputs are well covered by the schema and the description. It could add explicit exclusions or rate-limit notes, but for this complexity it is sufficiently complete.

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 the baseline is 3. The description adds value by explaining how parameters map to algorithm criteria, e.g. nationality drives 'visa accessibility' and field drives 'field alignment.' It also benefits from the schema's converted_gpa hint to 'use convert_gpa first,' which adds cross-tool semantic meaning.

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 a specific verb and resource: 'Get personalised, ranked scholarship recommendations for an African student based on their full profile.' It further distinguishes the tool from generic search by naming the matching algorithm and ranking criteria, so an agent can easily differentiate it from siblings like search_scholarships.

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?

It clearly defines the appropriate use case: personalized matching for African students with a full profile. However, it does not explicitly state when NOT to use it or mention alternatives by name, such as 'use search_scholarships for filtered lookup.' This is clear context but lacks explicit exclusions.

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