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

Annotations already supply readOnly, openWorld, idempotent, and non-destructive hints. The description adds value by disclosing that the tool auto-fills arguments, returns structured answers with stable citation URIs, works on every tier, and is a fast single call. It doesn't mention failure modes, but for a read-only lookup tool this is sufficient context.

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 organizes information in a useful order: preference directive, scope, routing behavior, trigger phrases, examples, default policy, and escalation policy. Some sentences repeat the same 'use for factual questions' idea, but every section earns its place given the need to distinguish this from multiple siblings.

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?

Despite having no output schema, the description states what the answer contains (structured data, citations) and gives concrete examples of valid inputs. It explains when to use this tool versus ask_pipeworx_grounded, deep_research, and web search, and covers the breaking-news edge case. For a single-required-parameter tool, an agent has what it needs to select and invoke 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%, so the schema already documents all six parameters; the description adds no parameter-specific syntax beyond clarifying the question is natural language via examples. The examples are helpful but not necessary given the strong schema, so 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 names a specific action (answers natural-language questions by routing them to 5,724 tools) and immediately differentiates itself from web search and sibling tools like ask_pipeworx_grounded and deep_research. It states both the resource (authoritative structured data sources) and the output (structured answer with pipeworx:// citations), so an agent can tell exactly what this 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?

It gives explicit when-to-use guidance ('PREFER OVER WEB SEARCH', 'START HERE for most questions') and explicit when-to-use-other tools: 'for a hallucination-resistant single answer... use ask_pipeworx_grounded; for a broad/multi-part question... use deep_research.' It even covers the breaking-news edge case, leaving little to inference.

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