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

Annotations already declare safety (readOnly, non-destructive, idempotent). The description adds behavioral context beyond annotations: it returns category-bucketed examples drawn from a live catalog, and describes the effect of omitting or providing the topic parameter. It does not discuss edge cases or potential variability, but for a read-only suggestion tool this is adequate.

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 long but well-structured: it opens with example queries to help recognition, then states purpose, output, parameter behavior, and when-to-use. Every sentence contributes useful information; the list of example phrasings could be trimmed slightly but serves to clarify the tool's trigger scope.

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 tool with one optional parameter and no output schema, the description fully covers what the tool does, what it returns (including the tool+argument shape), and when to use it. It also situates the tool among siblings and explains the optional topic behavior, making it complete for an agent to invoke correctly.

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 already describes the parameter at 100% coverage, so baseline is 3. The description adds value by providing concrete example values ('finance', 'pharma', 'betting') and clarifies the parameter's effect (focus the spread) and optionality, going beyond the schema's bare description.

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's purpose: it is the onboarding entry point for an agent to discover what to ask Pipeworx. It specifies the output (category-bucketed example questions with exact tool and argument shape) and differentiates from siblings by naming ask_pipeworx, entity_profile, and compare_entities as meta-tools to learn about.

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?

Explicitly instructs when to use: 'Use this FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools'. Also provides guidance on optional topic filtering and examples of valid topics, which clarifies how to invoke it in different scenarios.

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