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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive, and the description adds substantial behavioral context: the output structure (category-bucketed examples with tool+argument shapes), that it is drawn from a live catalog of thousands of tools, and how invocation with or without `topic` changes results. No contradiction with 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 dense and front-loaded, with every sentence contributing either example queries, return behavior, or usage guidance. The list of categories is long but informative; minor verbosity in the opening example string is acceptable given the tool's onboarding purpose.

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 purpose, behavioral details, invocation patterns, and parameter semantics. It gives the agent enough to understand expected response structure and when to use it, especially in context of sibling meta-tools.

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 schema covers the single optional `topic` parameter with a list of values, and schema description coverage is 100%. The description reinforces parameter meaning with examples ('finance', 'pharma', 'betting') and explicitly explains the behavior when omitted (full spread), adding value beyond the schema.

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 role as the onboarding entry point, lists example user queries, and explains it returns category-bucketed example questions with exact tool and argument mappings. It distinguishes itself from siblings by explicitly naming meta-tools and positioning itself as the first thing to use.

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 explicit when-to-use guidance: 'Use this FIRST when you do not yet know what Pipeworx can do for you.' It also names alternative tools (ask_pipeworx, entity_profile, compare_entities) to learn how to call them, providing clear context on when this tool is appropriate versus alternatives.

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