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

Annotations already declare readOnly, idempotent, closed-world, and non-destructive behavior, so the safety profile is covered. The description adds useful scope detail ('between consecutive presentations') and characterizes the diff dimensions, though the output schema already carries the return structure, so this is additive rather than essential.

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, front-loaded with the core action ('Compare... across periods') followed by output scope and activation cues. Every clause carries information; no filler or repetition of the 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?

With a rich annotation set and a present output schema, the description need only cover purpose, scope, and when-to-use, which it does. The one gap is absence of sibling disambiguation, which matters given the dense cluster of language/narrative tools.

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% – the single 'ticker' parameter is documented in-schema as an NZX symbol with an example. The description adds no syntax, format, or constraint beyond that, so the schema does the heavy lifting and baseline 3 applies.

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: 'Compare earnings presentation transcripts across periods,' and enumerates the output categories (language diffs, tone shifts, sentiment changes). It is clearly not a tautology. However, it does not distinguish itself from plausibly overlapping siblings such as get_section_evolution, get_narrative_tracker, or get_disclosure_language, which map to similar language-change concepts.

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?

It gives explicit triggering contexts: 'Use when asked about management language changes, tone shifts, how earnings presentations have changed, or credibility tracking.' This is clear context for activation, but there is no when-not guidance and no named alternative among the many language/narrative siblings.

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