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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so safety is covered. The description adds valuable context: it returns a structured list of example questions with tool+argument shapes, drawn from a live catalog, and explains the behavior with/without the topic argument. This goes beyond the annotations but doesn't disclose limits like freshness or pagination, which are not needed here.

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 somewhat long but well-structured: it starts with natural language query examples, then explains the return value, usage, and when to use it. Each sentence contributes meaning, though the initial list of queries could be trimmed for brevity. It is front-loaded with the tool's 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?

Without an output schema, the description fully explains the return format (category-bucketed example questions with tool+argument shapes). It covers call variants, parameter behavior, and usage context. Given the tool's moderate complexity, the description is complete and self-contained.

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 input schema already provides 100% coverage for the single optional 'topic' parameter with a description. The description adds further meaning by giving concrete example values ('finance', 'pharma', 'betting'), explaining that omitting it returns the full spread, and clarifying that the topic focuses the returned categories. This is above the baseline for complete schema coverage.

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 that this is the onboarding entry point for an agent, returning category-bucketed example questions with exact tool and argument shapes. It explicitly differentiates from sibling tools like ask_pipeworx and entity_profile by positioning itself as the 'first use' tool when the agent doesn't know what Pipeworx can do.

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 usage 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 (ask_pipeworx, entity_profile, compare_entities, etc.).' It also explains optional topic filtering and when to omit it, making the decision context clear.

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