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

Annotations already cover read-only/non-destructive, yet the description adds substantial behavior: whole-word and case-insensitive matching, hyphen/join equivalence, CJK and empty transcripts flagged rather than zeroed, the Q&A split only when a hand-off is stated, and a capped output of one or two quotes. These are exactly the caveats an agent would otherwise misreport.

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 core action and output shape before the edge-case rules. It is dense but a single long sentence, and the hyphen/join rules duplicate the schema rather than earning new space.

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 no output schema, the description does the work of describing the return payload (mentions per call, rate per 10,000 words, prepared-remarks/Q&A split, sample quotes). Combined with annotations covering safety, an agent has everything needed to call and interpret it.

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 schema already documents all three parameters in detail. The description adds only the ordering of the `calls` window ('oldest first') and largely restates the phrase-matching rules already present in the phrase schema — a 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?

Names a specific verb ('count how often a word or phrase comes up') and resource (a company's last earnings calls), plus the exact scope ('last N calls, oldest first'). This is clearly distinct from the sibling transcript tools (GetEarningsCallTranscript returns full text, GetEarningsCallThemeHistory follows themes) without needing to name them.

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?

'Use it to follow a product, risk or initiative across quarters' gives a concrete usage context. However, it names no alternative tool and no when-not condition, so an agent must still infer the boundary with GetEarningsCallThemeHistory and GetEarningsCallTranscript.

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