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

The description discloses key behavioral traits beyond the sparse annotations: it runs a live web search, has higher latency and cost, and returns a verification warning because scholarship programs change. It also positions the output as a research starting point, which sets accurate expectations about reliability. The annotations provide little behavioral coverage, so this description carries the burden well.

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 compact: two substantive sentences plus a cost line. The main purpose is front-loaded, followed by necessary caveats and operational cost. No filler or redundant restatement of the tool name.

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 live-search tool with no output schema, the description covers the key decision factors: what it returns, why it's slower and pricier, and how trustworthy the output is. The main gap is that, with zero required parameters, it doesn't state what minimal inputs are needed or how the output is structured beyond 'scholarships and application angle.'

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 description coverage is 88%, so the structured schema already documents most parameters and even adds strategic context such as 'departmental awards are usually the least contested.' The description itself does not elaborate on parameters, but the schema compensates adequately, leaving this at the baseline.

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 a concrete action: 'Surface scholarships worth this student's time and the angle their application should take for each.' This clearly defines the output and intent. It distinguishes itself from generic matching by mentioning live web search and 'other analysis tools,' but it does not name specific sibling tools, so sibling differentiation is incomplete.

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 warns that the tool is slower and more expensive than other analysis tools and frames the result as a research starting point, giving the agent a clear sense of when to use it. However, it does not name alternative tools or explicitly state when not to use this tool.

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