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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds that the source is 'Stratalize market intelligence composite' and gives a detailed example of the output format (GROWING signal, citation shares, disruption risk), which enriches understanding beyond the annotations.

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 four sentences: usage, return summary, concrete example, and source attribution. Every sentence adds value with no redundancy, and the most important usage guidance 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?

The description explains what the tool returns and provides a concrete example of the output structure, which is critical since no output schema is available. It lacks detail on the exact response format (e.g., JSON structure) but is sufficient for tool selection and 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?

The schema has a single 'category' string with no description. The description clarifies it is a software category and provides 'CRM' as an example, which adds crucial semantic meaning. However, it does not enumerate valid categories or formatting expectations, so it falls short of a perfect score.

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 clearly states the tool returns growth signal, AI citation leaders, and disruption risk for a SaaS category, with a concrete CRM example illustrating each output. This distinguishes it from sibling tools that focus on individual signals (e.g., get_category_ai_leaders, get_category_disruption_signal).

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 opening sentence 'Use when assessing a SaaS category investment thesis, competitive dynamics, or market momentum before a strategic decision' provides clear usage context. It does not explicitly mention alternatives or exclusions, but the context is sufficient for most scenarios.

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