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

The description adds significant context beyond annotations: it explains the tool returns example questions with exact tool+argument shapes, drawn from a live catalog of thousands of tools. It also details the behavior of no-argument vs topic-specific calls. No contradiction with annotations (readOnlyHint true, etc.).

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 one long but information-dense sentence. It front-loads the purpose with common user queries. However, it could be broken into clearer sections for readability. 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?

Given no output schema, the description clearly explains what is returned: category-bucketed example questions with tool+argument shapes. It also covers the param behavior and use case thoroughly. No gaps for a discovery/onboarding 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?

The description adds meaning to the 'topic' parameter by listing concrete focus areas (e.g., 'finance', 'pharma', 'betting') and explaining that omitting the parameter gives a cross-category spread. Since schema coverage is 100%, the baseline is 3, and the description provides additional context, justifying a 4.

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 it is an onboarding entry point, returns category-bucketed example questions (e.g., 'company financials', 'drugs & clinical trials'), and helps the agent understand what Pipeworx is good for. It uses specific verbs like 'returns' and lists actionable categories, distinguishing it from sibling tools like ask_pipeworx or entity_profile.

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 explicitly says 'Use this FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools'. It also explains when to omit topic for a full spread or specify a topic for focus. It does not explicitly state when not to use it, but the context is clear.

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