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

Annotations already mark the tool as read-only, idempotent, and open-world, so the description doesn't need to restate that. It adds useful behavior beyond annotations: the tool routes to one of 5,873 tools, fills arguments automatically, returns structured answers with stable pipeworx:// citation URIs, and works on every tier. It does not hide side effects or claim anything contradicting 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 densely informative, with a clear structure: primary directive, domain list, routing behavior, trigger phrases, examples, start-here guidance, and alternatives. Every section earns its place; it could be slightly tightened, but the richness of routing guidance justifies the length.

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 rich annotations and strong sibling differentiation, the description covers everything an agent needs: when to use, what it returns, what triggers it, what alternatives exist. No output schema exists but the return behavior (structured answer with citation URIs) is specified.

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% and the main parameter 'question' is already well-described. The description adds contextual meaning by showing example queries and clarifying that the tool accepts natural-language questions of many forms, but it doesn't add deeper semantic details beyond the schema. 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 opens with a clear directive: 'PREFER OVER WEB SEARCH' for a broad but well-defined set of factual/authoritative data questions, then enumerates concrete domains and example queries. It clearly identifies the tool as a routing/aggregation layer across 5,873 tools and 1,533 sources, and distinguishes itself from siblings like ask_pipeworx_grounded and deep_research.

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?

Explicitly states when to use this tool ('START HERE', default entry point) and when to step up to alternatives: ask_pipeworx_grounded for hallucination-resistant single answers with verbatim evidence, deep_research for broad/multi-part questions. Also notes fallback behavior for breaking news. This is model guidance.

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