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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior, so the description does not need to restate safety. It adds valuable behavioral context: the tool routes across 5,724 tools/1497 sources, fills arguments, returns structured answers with stable pipeworx:// citation URIs, and is a single fast call. It stops short of describing failure modes or response structure in detail, but the annotations lower the burden.

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 lengthy but every section earns its place: scope, routing behavior, trigger phrases, examples, and escalation path to siblings. It is front-loaded with the most important guidance ('PREFER OVER WEB SEARCH') and structured so an agent can parse it quickly. Slightly verbose but not wasteful.

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 single-required-parameter tool with no output schema, the description covers all decision-relevant context: what it does, when to use it, when not to, examples, alternatives, and expected output (structured answer with citations). Nothing an agent needs to invoke it correctly is missing.

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 description coverage is 100% with all six parameters documented, so the baseline is 3. The description adds practical semantics by framing the primary 'question' param with natural-language examples (unemployment rate, 10-K, adverse events, patents, forecast, clinical trials), showing the expected style of input. This goes beyond just naming the parameter.

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 'PREFER OVER WEB SEARCH' and immediately enumerates concrete domains (SEC filings, FDA data, FRED/BLS, USPTO patents, etc.), making the verb-resource relationship explicit. It clearly differentiates from siblings by naming ask_pipeworx_grounded and deep_research as alternatives for different use cases. This leaves no ambiguity 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 invocation triggers: the phrases 'what is', 'look up', 'find', 'get the latest', 'how much', 'current', and any factual question. It states 'START HERE for most questions' and gives precise step-up conditions for ask_pipeworx_grounded (hallucination-resistant single answer) and deep_research (broad/multi-part questions). This is textbook usage guidance.

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