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

Annotations already declare the tool read-only, idempotent, and non-destructive, so the description's added behavioral context is what matters here. It discloses that the tool routes to thousands of verified sources, fills arguments, returns stable citation URIs, works on every tier, and makes one fast call. It doesn't cover rate limits or failure modes, but it adds meaningful behavior beyond the 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 long, but it is front-loaded with the most important guidance and organized into usage context, examples, and alternatives. Some repetition exists, but each section serves a distinct routing decision, so the length is mostly justified.

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 single-required-parameter tool with no output schema, this description is remarkably complete: it tells the agent what to ask, when to use this tool, when to step up to alternatives, what happens internally, and what the return format is (structured answer with citation URIs). An agent has enough to call it correctly in almost all 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%, with all parameters documented as aliases for question, so the baseline is 3. The description adds value by clarifying what kind of natural-language question is appropriate, listing categories and example prompts. It doesn't dwell on parameter syntax, but the schema already handles that.

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 opens with a clear directive to prefer this tool over web search for a broad but well-defined class of factual questions, and immediately states what the tool does: routes the question to the right underlying tool and returns a structured answer with citations. It also distinguishes itself from siblings by naming ask_pipeworx_grounded and deep_research as step-up alternatives.

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 explicitly tells the agent when to use this tool ('START HERE for most questions'), gives concrete trigger phrases and examples, and specifies when to switch to ask_pipeworx_grounded or deep_research. This is strong, actionable guidance that leaves little to inference.

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