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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only says it generates an FAQ with AI; it does not explain how docs/content/count relate to the output, whether a count is required or optional, what the return format is, or any limitations. The description adds little behavioral context beyond restating the tool's name.

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 concise and front-loaded, with one short sentence stating the core purpose. It earns a 4 rather than 5 because of minor redundancy: 'AI FAQ', 'FAQ', and 'with AI' repeat information already implied by the tool name and purpose.

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 tool has three optional string parameters, no annotations, and no output schema, so the description needs to compensate for a lot of missing context. It does not explain how many FAQs are generated, how count is interpreted, what input should go into docs vs content, or what the response looks like. This is not complete enough for an agent to reliably invoke the tool.

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 baseline is 3. The tool description adds only the vague notion of generating from a 'topic', while the schema parameters are named docs, count, and content. It does not clarify what 'count' means, how docs differs from content, or how a topic should be supplied, so it adds no meaningful parameter semantics beyond the schema.

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 a specific action and resource: generate an FAQ from a topic using AI. It is distinguishable from most sibling AI tools because the expected output is an FAQ. However, it loses a point because the input schema refers to docs/content/count rather than a 'topic', so the described input model does not exactly match the actual parameters.

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 implies a usage context—whenever an FAQ needs to be generated from a topic—but gives no explicit guidance about when to choose this tool over alternatives, what kind of topic/docs/content is expected, or when not to use it. No alternative tools or exclusions are mentioned.

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