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

Annotations provide readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, and the description adds substantial behavior beyond these: parallel faceted decomposition, findings packet structure, explicit gaps[] that are never invented, contradictions[] for standard/thorough, hop fields, citation_uri fetchability, semantic excerpting, and latency expectations. This fully discloses operation without 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 every sentence earns its place: it front-loads the critical account requirement, then covers functionality, usage boundaries, depth behaviors, return format, and latency. There is no filler; the structure logically moves from prerequisites to when-to-use to how-it-works to expectations.

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?

With no output schema, the description fully documents the return packet: verbatim evidence, confidence, source, fetched_at, pipeworx:// citation, gaps[], contradictions[], hop field, and citation_uri. It also covers prerequisites, alternatives, edge cases, and runtime expectations, making it complete for both calling and interpreting results.

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 baseline is 3, but the description adds meaning beyond the enum descriptions: it explains how each depth value behaves ('standard' re-angles gaps, 'thorough' chases leads), provides example questions, and clarifies that broad/multi-part questions are the intended use. This is a meaningful addition over the schema.

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 specific verb and resource: 'Grounded multi-source research across Pipeworx's 1497 STRUCTURED data sources... in ONE call.' It clearly distinguishes itself from siblings by explicitly naming ask_pipeworx as the alternative for single lookups and current news, and it positions itself as 'NOT open-web search.'

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 when-to-use and when-not-to-use guidance: 'Best for broad/multi-part questions over structured data,' and 'For a single lookup use ask_pipeworx... For BREAKING or colloquial CURRENT-NEWS... prefer ask_pipeworx.' It even handles the account prerequisite: 'If you are not signed in, use ask_pipeworx instead.'

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