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

The description goes far beyond the annotations by adding concrete behavioral details: auth prerequisite, paid-plan requirement for thorough, expected latency (15-90s), decomposition and parallel routing, return field semantics (evidence, confidence, source, fetched_at, citations, gaps[]), the never-invented guarantee, contradictions[] behavior for standard/thorough, and semantic excerpting of large records. None of this is contradicted by 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 dense and front-loaded with the most decision-critical facts (auth and alternative tool) before getting into mechanics. It is longer than necessary and partially repeats depth-mode details already present in the schema, plus a few convoluted phrasings, but nearly every sentence earns its place for a tool with no output schema.

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 tool with no output schema, the description fully compensates: it explains the return packet contents, citation semantics, gap handling, contradiction behavior, latency, depth modes, auth requirements, and when to use a sibling tool. An agent has what it needs to decide, invoke, and interpret results 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?

With 100% schema_description_coverage the bar is high, but the description still adds real value: it explains the depth enum interpretations (quick=3 single hop, standard=3 default with gap recovery + contradictions, thorough=6 full iterative hop + contradictions) and the fact that depth:'thorough' is paid. It also clarifies that question is natural language and can be broad/multi-part because decomposition is the point.

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: it performs grounded multi-source research across 1517 structured data sources, decomposes questions into facets, routes them in parallel, and returns a findings packet. It also distinguishes itself from open-web search and names ask_pipeworx as a sibling alternative, so an agent can tell them apart without opening 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?

Explicit when-to-use guidance is present: best for broad/multi-part questions over structured data, and for a single lookup use ask_pipeworx instead. It also gives a strict exclusion condition: if not signed in, use ask_pipeworx because it works on every tier. This is enough to route an agent reliably.

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