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

Even with strong annotations (readOnly, openWorld, idempotent), the description adds exceptional behavioral context: latency expectations ('15-60s... up to ~90s'), hallucination-avoidance policy ('explicit gaps[]... never invented'), citation-fetchability honesty (citation_uri present 'only when the source emits one that resources/read can actually serve'), contradiction scanning, and semantic excerpting instead of head-truncation. This goes far beyond what annotations convey.

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 the most critical constraint (ACCOUNT REQUIRED) is front-loaded. However, the description is one dense run-on paragraph with heavy parentheticals, em-dashes, and semicolons, mixing prerequisites, methodology, return format, depth semantics, and latency into a single wall of text. Logical section breaks would substantially improve parseability.

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 complex tool with no output schema, the description covers everything needed to call it correctly: findings-packet contents, gaps[] behavior, citation provenance guarantees, depth-tier behavioral differences, account/pricing prerequisites, and timing. The only minor omissions (quick-tier prose, error cases) are covered by the schema or non-essential.

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% and both parameters are already well-documented in the schema. The prose adds behavioral meaning to the depth parameter beyond the enum descriptions — paid-tier requirement for thorough, hop semantics ('re-angles unanswered gaps', 'chases the best leads from the first pass'), and latency implications — and reinforces the question parameter's latitude ('broad/multi-part is fine — 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 precise verb and resource: 'Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources... in ONE call.' It actively distinguishes the tool from siblings by asserting 'this is NOT open-web search' and naming ask_pipeworx as the single-lookup 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?

Usage conditions are fully explicit: '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 states what it is best for ('broad/multi-part questions over structured data') and which depth tier requires a paid plan. No inference is needed to choose between tools.

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