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

Annotations already declare read-only, idempotent, non-destructive behavior. The description adds value by describing the return format: 'Returns category-bucketed example questions... each with the exact tool + argument shape,' and notes the output is 'drawn from the live catalog of thousands of tools,' implying dynamic content. This contextualizes what the agent can expect without contradicting the 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?

While the description is longer than average, every sentence earns its place: it lists user intentions, return contents, category names, parameter behavior, and a clear 'Use this FIRST' directive. It is well-structured with the opening queries, a dash explanation, and a closing usage statement. No fluff.

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 only one optional parameter and no output schema, the description is complete: it explains what the tool does, what it returns, how to call it, and when to use it. It also references related meta-tools, providing full onboarding context. There is no missing information needed for an agent to select and invoke this tool 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 coverage is 100%: the only parameter `topic` is fully described with allowed values and the omit behavior ('Omit for a cross-category spread'). The description repeats this and adds examples ('finance', 'pharma', 'betting'), but does not introduce new meaning beyond what the schema already provides. Baseline 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 clearly states the tool is the onboarding entry point that returns category-bucketed example questions each with the exact tool and argument shape to answer it. It distinguishes itself from siblings like ask_pipeworx and discover_tools by focusing on 'what is worth asking' and learning how to call meta-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?

Explicit direction is given: '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 two calling modes: no arguments for the full spread, or pass a topic to focus. It does not mention explicit alternatives or when not to use it, so not a 5.

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