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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is known. Beyond that, the description adds useful behavioral context by explaining the return structure: category-bucketed example questions with tool and argument shape, drawn from the live catalog. It also notes that no arguments returns the full spread, which is behavior not covered by annotations.

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 front-loaded with example queries, quickly establishes purpose, and then details output and usage. Although slightly long, every sentence adds value—covering output content, parameter usage, and the recommended first-use scenario. It is well-structured and not redundant.

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 simple one-parameter tool with no output schema, the description is remarkably complete: it explains what the tool returns, how to invoke it, and when to use it. It even lists the major category examples. Minor gap: it doesn't specify the exact JSON response shape, but the description of each item's contents suffices for an agent to understand the return value.

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 description coverage is 100% for the single `topic` parameter, and the schema already explains the allowed focus areas and the omit-for-full-spread behavior. The description reinforces this with examples ('finance', 'pharma', 'betting') but does not add meaningful new information beyond the schema, so it meets the baseline of 3.

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 states a specific verb and resource: it returns category-bucketed example questions from the live catalog, each with the exact tool and argument shape. It distinguishes itself from siblings by positioning as the onboarding entry point and explicitly referencing 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 gives clear 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 explains the optional `topic` parameter for focusing. It implies when not to use it (if you already know what to ask), but does not name specific alternative tools as exclusions.

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