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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, covering the safety profile. The description adds valuable behavioral detail beyond that, such as the return format (category-bucketed example questions) and that each result includes the exact tool and argument shape. It also clarifies the live catalog source and how to narrow by topic.

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?

Although the description is longer than typical, it is densely packed with high-value information: query examples, output structure, usage modes, and onboarding guidance. It is well-structured with a clear flow (what it is, what it returns, how to call, when to use). Every sentence contributes meaning without redundancy.

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 is complete for the tool's complexity. It explains the purpose, output content (category-bucketed questions with tool+argument shapes), parameter behavior, and explicit when-to-use guidance. There is no output schema, so the description fully compensates by describing the return format. Annotations cover safety, so 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?

The schema already provides 100% coverage for the single optional 'topic' parameter, including a list of allowed values. The description adds marginal context by restating examples ('finance', 'pharma', 'betting') and explaining the default behavior (cross-category spread), but does not fully go beyond the schema's own description. Baseline of 3 is appropriate.

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 uses a specific verb+resource ('suggest questions') and clearly defines the tool's scope as the onboarding entry point for discovering what Pipeworx can do. It distinguishes itself from siblings by explicitly stating it returns category-bucketed example questions with exact tool+argument shapes, and by naming meta-tools like ask_pipeworx and 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 provides explicit when-to-use guidance: '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 clarifies the no-argument vs topic-argument usage and gives examples of topics, making it clear how to invoke the tool in different contexts.

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