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

Annotations already declare readOnly/openWorld/idempotent/non-destructive, so the description only needs to add invocation and output behavior. It does: says it draws from a live catalog of thousands of tools, returns category-bucketed examples each with tool + argument shape, and can be called with no args for full spread or with topic to focus. No contradictions 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 densely packed but well-structured: opening with user intents, then the return value, then invocation modes, then when to use. It is longer than minimal, but every sentence adds necessary context for a tool with no output schema and rich categorization behavior.

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?

With no output schema, the description appropriately details the return value: category-bucketed example questions across clearly named categories, each with the exact tool and argument shape needed. It also covers both invocation modes and the onboarding context. Combined with annotations, it gives a comprehensive picture of what to expect, though a concrete example of the output shape would push it to 5.

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%, but the description enriches the parameter 'topic' with concrete examples ('finance', 'pharma', 'betting') and explains the effect of omission ('cross-category spread'). This goes beyond the schema's basic description and helps the agent select and format the parameter correctly.

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 opens with concrete example questions, then clearly defines the tool as the onboarding entry point for agents that want to know what to ask Pipeworx. It distinguishes itself from siblings by explaining it returns category-bucketed example questions with the exact tool and argument shape from a live catalog, and explicitly says to use it FIRST.

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?

Provides explicit 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 and names alternatives like ask_pipeworx, entity_profile, and compare_entities as examples of what the agent will learn to call, giving clear situational context.

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