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

Annotations already declare read-only, open-world, idempotent, and non-destructive behavior. The description adds useful context by explaining that results are category-bucketed example questions with exact tool+argument shapes, drawn from a live catalog, and that calling with no arguments returns the full spread. This goes beyond basic annotation coverage.

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 a single dense paragraph that front-loads user-facing questions and clearly separates behavioral details. It is efficient in listing categories and examples, though it could be structured with line breaks for improved scannability. Overall, it earns its length.

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?

Despite having no output schema, the description thoroughly explains what the tool returns (category-bucketed example questions with tool+argument shape), how to invoke it (with or without topic), and its role in the broader agent workflow. It fully covers the context needed to use the tool effectively.

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 already provides 100% coverage for the optional `topic` parameter with a comprehensive list of options. The description reiterates the parameter ('pass topic') and gives a few examples, but adds little meaning beyond the schema. Baseline 3 is appropriate since the description neither compensates for gaps nor contradicts 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 the tool as an onboarding entry point that suggests example questions, listing concrete intents ('What can I ask Pipeworx?', 'what can you do?'). It distinguishes itself from siblings like ask_pipeworx by framing it as a discovery aid rather than an answering tool.

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?

Explicitly instructs 'Use this FIRST' when unfamiliar with Pipeworx, and points to learning meta-tools such as ask_pipeworx, entity_profile, and compare_entities. However, it does not explicitly state when NOT to use it (e.g., for direct factual queries), so it lacks a clear exclusion boundary.

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