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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, destructiveHint, so the safety profile is clear. The description adds useful behavioral context: the tool is the onboarding entry point and returns example questions with tool calls. It does not describe rate limits or auth needs, but those are not relevant for a read-only tool. The description complements annotations well.

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 relatively long but every sentence serves a purpose: it provides example user queries, explains the return format, gives invocation instructions, and positions the tool relative to siblings. It could be slightly tighter, but the front-loading with common questions is effective for agent understanding.

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?

Given the tool's simplicity (one optional parameter, no output schema), the description covers all necessary aspects: purpose, usage, parameters, return value, and relationship to sibling tools. It tells the agent exactly what to expect and how to use it. No gaps remain.

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 coverage is 100%, so the schema already describes the topic parameter. The description adds value by explaining that omitting the topic gives a 'cross-category spread' and enumerating the exact allowed values (finance, pharma, etc.), giving more context than the schema's enum list.

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 category-bucketed example questions with tool+argument shape, explicitly positioning it as the onboarding entry point. It distinguishes itself from sibling tools like ask_pipeworx and deep_research by advising 'Use this FIRST when you do not yet know what Pipeworx can do for you.'

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 provides explicit when-to-use guidance ('Use this FIRST'), includes two invocation patterns (no arguments vs. with topic), and lists alternative tools such as ask_pipeworx, entity_profile, and compare_entities. It clearly states what the tool is for and when to prefer it.

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