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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior. The description adds valuable context beyond those hints by disclosing that results are drawn from a 'live catalog of thousands of tools' and that each example includes 'the exact tool + argument shape' that answers it. This is useful behavioral detail without contradicting 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 longer than ideal but front-loaded with example queries and organized with dash-separated category lists. Every sentence carries functional value: purpose, return contents, parameter behavior, and onboarding usage. It is comprehensive without being bloated, though tighter phrasing would improve it.

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 1 optional parameter, no output schema, and clear annotations, the description is fully complete. It explains what the tool returns (category-bucketed questions with tool+argument mappings), how to call it (no args or with topic), when to use it (first when onboarding), and what it helps the agent learn (meta-tools). No important context is missing.

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 of the single parameter (topic), including the allowed focus areas and the behavior when omitted. The description repeats these examples ('finance', 'pharma', 'betting') and the omit behavior, adding no new semantic information beyond the schema. This meets the baseline for high 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 uses a specific verb ('Returns category-bucketed example questions') and clearly identifies the resource (Pipeworx tool catalog) and the onboarding scope. It distinguishes itself from sibling tools by positioning itself as 'the onboarding entry point' and explicitly saying to 'Use this FIRST' when unsure 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 gives clear when-to-use guidance ('when you do not yet know what Pipeworx can do for you') and explains the optional topic parameter with example focus areas. It does not explicitly name alternatives such as discover_tools or ask_pipeworx as 'use this instead,' but the 'FIRST' directive and onboarding framing provide strong contextual placement.

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