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

Beyond the safe-read annotations (readOnly, idempotent), the description discloses the return shape (category-bucketed questions with tool shapes), the effect of the topic parameter (focus vs. full spread), and that it draws from the live catalog of thousands of tools. This adds substantial behavioral context that annotations alone do not provide.

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 dense but front-loaded with example queries and packs function, usage, and parameter behavior into a single paragraph. While every sentence carries information, the structure is a run-on with em-dashes; splitting into clearer sentences would improve readability without losing content.

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 simple one-parameter tool with comprehensive annotations and no output schema, the description fully covers the return value (category-bucketed questions with tool shapes), call patterns (with/without topic), and when to use it first. The sibling context further supports tool selection, making the description complete for this tool's complexity.

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 covers the topic parameter fully (100% coverage) with its list of focus areas and 'Omit for a cross-category spread.' The description adds examples ('finance', 'pharma', 'betting') and reinforces the behavioral effect (no args = full spread, topic = focus), providing modest enrichment 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 states the tool is the onboarding entry point for learning what Pipeworx can do, returning category-bucketed example questions with the exact tool and argument shape. It explicitly distinguishes itself from siblings like ask_pipeworx (actual queries) and discover_tools by positioning itself as the 'FIRST' step, making its purpose unmistakable.

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 when-to-use 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 also names alternative tools (ask_pipeworx, entity_profile, compare_entities) for learning meta-tool usage, providing clear context for tool selection.

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