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

Annotations already declare readOnlyHint=true, so safety is covered. The description adds useful context that the output is counts plus engagement grouped by category, but says nothing about how categories are derived, whether uncategorized posts appear, or how metrics are computed.

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?

A single front-loaded sentence that names the metric, the grouping dimension, and the scope with no wasted words.

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 7 parameters and no output schema, the description should clarify the return shape (what counts, what engagement metrics, how results are grouped). It gives the gist but leaves the actual response structure ambiguous for an agent that must interpret results.

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 already documents every parameter including the enums and date formats. The description adds only the loose 'for companies or people' phrasing that maps to the source parameter, so 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?

States a specific resource (post counts and engagement per content category) and the entities it covers (companies or people), with concrete category examples. It is clear what the tool produces, though it does not explicitly differentiate itself from siblings like industry_landscape or company_fit_summary.

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 offers no when-to-use guidance, prerequisites, or alternatives. 'For companies or people' hints at scoping but never tells the agent when this breakdown is the right tool versus another aggregate view.

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