Best-value colleges by state

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

With no annotations, the description fully discloses the tool's behavior: it returns ranked lists (top 15 per state or top 1 per state), filters by resident pricing, and uses a specific metric (30-year NPV). This is comprehensive for the tool's simplicity.

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 wasted words. The first sentence defines the resource and ranking, the second specifies usage. Information is front-loaded and efficient.

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 tool with one optional parameter and no output schema, the description adequately covers behavior and output scope. It explains the ranking metric and the two modes. A minor gap is what 'best-value' precisely means beyond NPV, but it's sufficient for selection.

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 describes the 'state' parameter (two-letter code). The description adds semantic value by explaining how omitting the parameter changes the output (nationwide summary) versus providing it (full list per state). This enriches the parameter's meaning beyond the schema.

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 the tool's purpose: listing each U.S. state's best-value four-year colleges ranked by 30-year NPV, with a clear distinction between passing a state (top 15) or omitting it (nationwide top pick). This distinguishes it from sibling tools like get_college or search_colleges.

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 provides explicit guidance on when to pass a state ('for its full list') and when to omit it ('for a nationwide summary'). While it doesn't compare to sibling tools, the usage context is clear and sufficient for a single-parameter tool.

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