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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world behavior, so the safety profile is covered. The description adds one useful behavioral fact — results are scoped to the linked Market Brew account — but says nothing about return shape or pagination defaults.

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 short sentences with the usage trigger front-loaded and no filler. It could be marginally tighter but every sentence carries information.

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?

For a simple, optional-parameter list tool whose annotations cover safety and whose schema documents filtering, the description supplies the needed usage trigger and the account-scoping constraint. No output schema exists, but for a list endpoint the missing return detail is minor.

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 query parameter and its name/pageSize/offset filters are fully documented in the schema. The description adds no parameter meaning beyond that, so the baseline of 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 verb (list) and resource (Knowledge Bases), so the core action is unambiguous. It does not differentiate from close siblings like count_knowledge_bases or get_knowledge_base, which would require the agent to infer the distinction.

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 this when the user asks to list Knowledge Bases" gives a clear trigger condition, which is more than most siblings offer. However, it names no alternatives or exclusions, so the agent must infer that count_knowledge_bases is for totals and get_knowledge_base for a single record.

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