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

The description discloses that results are category-bucketed example questions each with the exact tool + argument shape, drawn from the live catalog. It also explains the effect of passing topic (focus) versus no arguments (full spread). Annotations already cover read-only/idempotent hints, and the description adds output structure and catalog dependency without contradicting.

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 well-structured, starting with example queries, then purpose, output details, and usage guidance. Every sentence contributes actionable information and there is minimal redundancy, making it appropriately sized for an onboarding tool.

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?

Even without an output schema, the description explains what is returned (category-bucketed examples with tool+argument shape), how to use it (with or without topic), and when to use it (FIRST, learning meta-tools). Annotations cover safety, so the description is complete for its context.

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 fully describes the optional topic parameter with values and omit behavior (100% coverage). The description reiterates this with examples but adds no substantial new parameter semantics beyond what the schema already provides, so 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 returns category-bucketed example questions with exact tool and argument shape, and positions it as the onboarding entry point. It distinguishes from siblings by saying 'Use this FIRST' and mentions learning to call meta-tools like ask_pipeworx, entity_profile, providing a specific verb+resource with differentiation.

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 lists trigger phrases ('what can I ask Pipeworx?', 'what is Pipeworx good for?', 'give me ideas') and explicitly says to use it FIRST when you don't know capabilities, or to learn to call meta-tools. This gives clear when-to-use context and differentiates from alternatives like ask_pipeworx.

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