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

Annotations already declare readOnly, idempotent, and non-destructive, so the bar is lower. The description adds valuable behavioral context: it says the tool returns categories of examples, includes the exact tool and argument shape, and draws from a live catalog of thousands of tools. This goes beyond the annotations without contradicting them.

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 a single, well-organized paragraph that front-loads example queries, then explains the return value, parameter usage, and when to use it. Every sentence provides distinct value, and there is no redundant information.

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, this description is complete: it covers purpose, usage variants, parameter semantics, and output characteristics. It even names the meta-tools it helps learn, making it self-contained and sufficient for an agent to decide when and how to invoke it.

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?

Although schema coverage is 100%, the description enriches the topic parameter by providing concrete examples ('finance', 'pharma', 'betting') and explaining the alternative of omitting it for a cross-category spread. This adds meaning beyond the schema's generic 'Optional focus area'.

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 ('returns') and defines the resource ('category-bucketed example questions with exact tool + argument shape'). It clearly distinguishes this from sibling tools by identifying it as 'the onboarding entry point' and recommending it 'FIRST' when unfamiliar with Pipeworx, unlike tools like ask_pipeworx or discover_tools.

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 states 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.' It also gives usage variations (no args vs. topic) and names alternatives (ask_pipeworx, entity_profile, compare_entities), making the guidance highly actionable.

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