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

Annotations already declare readOnly, idempotent, openWorld, and non-destructive behavior. The description adds that the tool draws from a live catalog of thousands of tools and returns example questions with exact tool and argument shape, plus topic filtering. This goes beyond the annotations by clarifying the dynamic, catalog-driven nature of the response.

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 strictly needed but front-loads the most important trigger phrases and purpose. Each sentence contributes distinct information: trigger examples, return structure, call variants, and when to use it first. It earns its length, though it could be tightened slightly without losing clarity.

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?

For a tool with a single optional parameter and no output schema, the description is complete: it covers what the tool returns, how to invoke it, when to use it, and how it relates to other meta-tools. The context signals and sibling list confirm the tool's role, and the description leaves no significant gaps in behavior or use cases.

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 coverage is 100% for the single optional `topic` parameter, and the description reinforces the 'omit for full spread, pass topic to focus' behavior. The description adds a few extra examples (e.g., finance, pharma, betting) but largely mirrors the schema's enum list. With high schema coverage, the baseline of 3 is appropriate; the description adds marginal but not substantial new semantic value.

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 this is the onboarding entry point for discovering what to ask Pipeworx, returning category-bucketed example questions with the exact tool and argument shape. It distinguishes itself from siblings like discover_tools and ask_pipeworx by emphasizing its role as a suggestions/ideas generator rather than a direct query or discovery 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?

Explicit usage guidance is provided: 'Use this FIRST when you do not yet know what Pipeworx can do for you' and for learning to call meta-tools. It also explains call variants—no arguments for the full spread vs. passing a topic to focus—and offers concrete trigger examples like 'give me ideas' and 'show me examples.'

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