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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive. The description adds useful behavioral context beyond this: it returns category-bucketed examples drawn from a live catalog, includes the exact tool and argument shape, and describes the optional topic-scoping behavior. It does not contradict the annotations and provides reasonable transparency for a read-only tool.

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 average but front-loads the most important user-intent phrases and quickly gets to the point. It covers purpose, usage, return value, and examples in a compact block. Some redundancy exists in listing many query phrasings and categories, but this is useful for an onboarding tool and not wasteful.

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?

Given there is no output schema, the description fully explains what the tool returns (category-bucketed example questions, each with tool + argument shape). It also covers argument behavior, the full vs focused call, and the intended first-use scenario. Combined with strong annotations, the description is complete and self-sufficient for an agent to select and invoke the 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 description coverage is 100%, so the baseline is 3. The description adds minor reinforcing detail ('pass topic to focus') and examples ('finance', 'pharma', 'betting'), but these largely mirror the schema's own description of the optional focus area and omitting for a cross-category spread. It does not provide meaningful new semantics 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 identifies this as an onboarding tool that returns category-bucketed example questions, and distinguishes it by explicitly stating the intended first-use scenario ('Use this FIRST when you do not yet know what Pipeworx can do for you'). It names the exact output (example questions with tool + argument shape) and references specific sibling meta-tools, making its purpose and differentiation clear.

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 usage context: 'Use this FIRST when you do not yet know what Pipeworx can do for you' and explains both calling modes (no arguments for full spread, or pass a topic to focus). It does not explicitly name alternatives or state when not to use it, so it stops short of a 5, but the guidance is clear and actionable.

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