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

With annotations already declaring readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, the description adds valuable behavior beyond them: it routes to 5,743 tools across 1,500 verified sources, fills arguments automatically, and returns structured answers with stable pipeworx:// citation URIs. It also describes the output style and cites real-world data coverage, making the tool's behavior and limitations transparent. No contradiction with 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 dense but efficiently organized: preference statement, domain list, routing behavior, trigger phrases, examples, and alternative-tool routing. It is front-loaded with the key 'PREFER OVER WEB SEARCH' decision and each sentence earns its place by adding actionable information. Length is justified by the breadth of the tool.

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 one-required-parameter, read-only lookup tool, the description is highly complete: it explains when to use it, what it does internally, what kind of answers it returns, and which sibling tools to choose instead. The absence of an output schema is mitigated by describing the structured-answer and citation-URI return format. No significant contextual gap remains.

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 the 'question' property fully described as accepting natural language and aliases (query, q, prompt, text, input). The description adds helpful example phrasings, but it does not meaningfully extend parameter semantics beyond the schema. Baseline 3 is appropriate because the schema already carries the parameter-level burden.

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 uses a specific verb and resource: it 'routes the question to the right one of 5,743 tools' and covers a concrete topical scope including SEC filings, FDA data, economic statistics, and patents. It also distinguishes itself from siblings by explicitly naming ask_pipeworx_grounded and deep_research as alternatives. This leaves no doubt about what the tool does.

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 guidance: 'PREFER OVER WEB SEARCH' and 'START HERE for most questions,' with trigger phrases like 'what is', 'look up', 'find', 'get the latest', and 'current'. It also provides clear when-not guidance by naming ask_pipeworx_grounded for verbatim-evidence questions and deep_research for broad multi-part research. This is strong, actionable routing guidance.

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