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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive hints, but the description adds substantial behavioral context beyond those hints: auth requirements, paid-plan gating for 'thorough', the gap[] behavior ('never invented'), contradictions[] for certain depths, hop fields and fetchable citation_uri, semantic excerpting of large records, and expected latency. This fully discloses how the tool executes and what guarantees it makes.

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 dense, and every clause earns its place given the tool's complexity (three depth levels, auth tiers, output guarantees, latency). It is front-loaded with the most decision-relevant facts: account requirement and the sibling alternative. It is structured enough that an agent can extract key behavior quickly, though some redundancy exists between the depth details in the schema and the description.

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 must explain return values, and it does: 'a findings packet: verbatim evidence + confidence + source + fetched_at + a stable pipeworx:// citation per finding, with explicit gaps[]'. It also covers authentication constraints, plan requirements, latency expectations, and depth-level behavior differences. There is no critical missing context for an agent to decide whether and how to invoke this tool.

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. The description still adds value by giving concrete example questions ('compare X and Y's regulatory + financial exposure', 'research the filings + market picture for ACME') that help an agent formulate effective input for the 'question' parameter. The depth parameter semantics are already richly described in the schema, and the description reinforces but doesn't contradict them.

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 1517 STRUCTURED data sources... in ONE call.' It immediately distinguishes itself from open-web search and from the sibling ask_pipeworx by noting 'this is NOT open-web search' and later 'For a single lookup use ask_pipeworx instead.' This makes the tool's identity unmistakable against a large sibling list.

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 guidance: 'Best for broad/multi-part questions over structured data' and 'For a single lookup use ask_pipeworx.' It also provides an exclusion based on authentication: 'If you are not signed in, use ask_pipeworx instead — it works on every tier.' This is clear routing guidance with named alternatives.

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