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

Annotations declare readOnly/idempotent/openWorld=false, but the description adds real behavioral context beyond them: the AND-in-any-order multi-word semantics, 'not paginated', the returned shape (yearly counts plus recorded award totals), and hard bounds. Contradicts nothing.

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?

Front-loaded with the trigger and examples, then constraints. Slightly dense in the middle clause but every sentence carries information an agent needs to call the tool correctly.

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?

Covered: trigger, match semantics, return shape, bounds, pagination. An output schema exists so return values needn't be detailed. Minor omission is the meaning of null fiscal year bounds, but the definition is otherwise sufficient for correct invocation.

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 0%, so the description must carry parameter meaning, and it does: query is REQUIRED and 2-64 chars, fiscal years 1985-2100, and start<=end. It omits explaining what happens when fiscal_year_start/end are null (default), a minor gap.

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+resource (topic funding trend over time) with concrete example queries, and distinguishes from siblings like funding_trend and funding_growth through the title-keyword framing and the 'how has a topic trended' use case.

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?

Gives explicit trigger phrasing ('Use this tool when the user asks how a research topic has trended over time') plus three example queries, but does not name the sibling alternatives (funding_trend, funding_growth) or clarify when-not to use it.

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