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

Annotations already mark this as read-only, idempotent, open-world, and non-destructive. The description adds valuable behavioral context beyond those flags: it routes across 5,724 tools and 1,497 sources, auto-fills arguments, returns structured answers with stable pipeworx:// URIs, works on every tier, and is a single fast call. No contradiction exists between the description and 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?

Despite being a fairly long paragraph, every sentence earns its place: it fronts the critical 'prefer over web search' directive, defines scope, gives concrete examples, establishes default status, and names alternatives. The structure is dense but highly scannable, with the most important decision guidance at the beginning.

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 default entry-point tool with several close siblings and no output schema, the description is complete: it covers when to choose it, what behavior to expect, what return format is produced, which alternatives to step up to, and which question categories it already handles. There are no obvious gaps that would prevent an agent from selecting and invoking it correctly.

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%: the single required question parameter and its aliases (q, text, input, query, prompt) are fully documented in the input schema. The description's examples of acceptable questions reinforce natural-language usage but do not add much beyond the schema's own examples and alias descriptions, so the baseline 3 is appropriate.

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 states a clear purpose: route a natural-language factual question to the right one of thousands of verified-source tools and return a structured answer with citation URIs. It explicitly differentiates itself from siblings like ask_pipeworx_grounded and deep_research, so an agent can immediately understand this is the default broad-router rather than a specialized variant.

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?

Usage guidance is exceptionally explicit: 'PREFER OVER WEB SEARCH', 'Use whenever the user asks...,' and 'START HERE for most questions' establish strong selection criteria. It also provides precise step-up alternatives: use ask_pipeworx_grounded for hallucination-resistant single answers and deep_research for broad/multi-part questions, plus a note that breaking-news questions are already covered.

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