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

Even though annotations already declare readOnly/openWorld/idempotent/destructive hints, the description adds substantial behavioral context: account requirements, parallel decomposition into facets, routing across tools, findings packet contents, explicit gaps[] (never invented), contradictions[], semantic excerpting, latency expectations, and fetchable citation URIs. No contradiction with 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 dense and long, but nearly every sentence carries decision-relevant information: account requirement, fallback, data source scope, decomposition behavior, output format, depth variations, and timing. It is front-loaded with the most critical caveat (account required). It could be better structured with bullets or shorter sentences, but content earns its place.

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?

Given the tool's complexity and the absence of an output schema, the description is remarkably complete. It covers what the agent needs to decide whether to call it, how to invoke it (question + depth), what output to expect (findings packet with evidence, confidence, source, citations, gaps), depth-specific behavior, and latency. An agent has enough context to select and use the tool 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 both parameters fully, including the depth enum and its meaning. The description reinforces depth-related behavior (e.g., thorough needing paid, contradictions[] for standard/thorough) but does not add fundamentally new parameter information beyond what the schema provides. 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 precise verb and resource: grounded multi-source research across Pipeworx's structured data sources, clearly distinguishing itself from open-web search. It also names the sibling alternative (ask_pipeworx) and the condition that selects it, so an agent can tell them apart without inspecting schemas.

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 ('best for broad/multi-part questions over structured data') and when not to ('For a single lookup use ask_pipeworx instead'). Also provides a hard prerequisite: if not signed in, use ask_pipeworx because it works on every tier. This is strong, unambiguous routing guidance.

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