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

Annotations already set readOnly/openWorld/idempotent/non-destructive, and the description adds behavioral context: it returns category-bucketed example questions with exact tool+argument shape, and it is drawn from a live catalog. It also explains the no-args vs topic behavior. 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 longer than one sentence but every clause adds value: usage triggers, parameter behavior, and output nature. It is front-loaded with example phrasings and ends with concrete instructions, though it could be slightly tightened without loss.

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 covers return contents (category buckets, example questions, tool+argument shape), invocation modes, and topic values. Combined with annotations, this gives an agent everything needed to decide when and how to call it.

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 topic with 100% coverage, so baseline is 3. The description adds meaning by giving examples ('finance', 'pharma', 'betting'), explaining that omitting returns a cross-category spread, and emphasizing that each result includes the tool+argument shape needed to ask. This elevates it above baseline.

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 suggest_questions as the onboarding entry point for a freshly connected agent, using specific verbs like 'Returns category-bucketed example questions' and 'Call with no arguments...'. It also distinguishes from sibling tools by positioning it as the FIRST tool to use and explicitly references meta-tools such as ask_pipeworx and entity_profile.

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?

It 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 explains when to omit vs pass topic, and names related tools (ask_pipeworx, entity_profile, compare_entities), giving clear context for selection.

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