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

Annotations already cover readOnly/openWorld/idempotent, and the description adds substantial behavioral context: auth requirements and paid plan, parallel decomposition, gap recovery, contradictions[] scanning, latency expectations (15-60s, up to ~90s), and the guarantee that gaps[] are never invented. It even discloses the nuance that citation_uri is present only when the source emits a fetchable URI. 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?

Every sentence earns its place and critical auth/alternative guidance is front-loaded. However, the prose is dense and heavily parenthetical, with semicolon-packed asides; the opening sentence combines account status, tier cost, alternative tool, and signup URL, making it harder to scan than necessary.

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 is unusually complete: it covers prerequisites, sibling alternatives, expected latency, output components (verbatim evidence, confidence, source, fetched_at, citation, gaps[], contradictions[], hop), and caveats (never invented, semantically excerpted records). Nothing an agent needs to decide when to use this tool or interpret its results is missing.

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 documents both parameters, but the description adds call-level meaning: depth tiers are tied to facet counts ('quick=3', 'standard=3', 'thorough=6'), the recovery/contradiction passes, and the paid-plan requirement for 'thorough.' It also clarifies that question is natural language and that multi-part phrasing is acceptable, which the schema implies but does not emphasize.

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' and explicitly says 'this is NOT open-web search.' It also states what it is best for ('broad/multi-part questions over structured data'), which clearly distinguishes it from open-web search and sibling lookup tools.

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 routing guidance: 'If you are not signed in, use ask_pipeworx instead — it works on every tier' and 'For a single lookup use ask_pipeworx instead.' It also explains the depth-tier tradeoffs, making it clear when each depth is appropriate.

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