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

Annotations already indicate readOnlyHint and openWorldHint, so the safety profile is covered. The description adds behavioral context beyond annotations: it explains the histogram bin range, notes that each bin includes representative article URLs, and clarifies that this is a snapshot distribution rather than a time series.

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 slightly longer than necessary but every sentence earns its place: it defines the output type, explains the analytical value, mentions bin contents, and differentiates from the sibling tool. The key scoping statement is front-loaded.

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?

With a rich output schema present and 100% parameter coverage, the description is complete for an agent to correctly invoke the tool. It adds the essential interpretive context (histogram semantics, bin contents, snapshot vs. time-series distinction) and names the relevant sibling, leaving no important gap.

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 100%, so the schema fully documents all four parameters. The description does not add new parameter meaning beyond what the schema already says, but it correctly references the query syntax without repeating the schema details. Baseline 3 is appropriate.

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 states a specific verb and resource: 'Get the tonal distribution of articles matching a query as a histogram.' It clearly distinguishes itself from gdelt_get_coverage_timeline by explicitly contrasting a snapshot distribution with a time series, so an agent can tell them apart without opening schemas.

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 gives explicit usage context: it explains when the histogram is valuable (uniformly negative, bimodal, neutral clustering) and explicitly names the alternative tool and condition for choosing it ('Use gdelt_get_coverage_timeline with mode "tone" to see how sentiment shifted over time').

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