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

Annotations already mark the tool as read-only, open-world, idempotent, and non-destructive. The description adds rich behavioral detail: parallel decomposition across 5,798 tools, findings packets with evidence/confidence/source/fetched_at/citation, explicit gaps[], contradictions[] for standard/thorough, citation_uri fetchability guarantees, semantic excerpting of large records, and latency expectations. Nothing contradicts 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 long but appropriately sized for a complex tool. It is front-loaded with the account requirement and the ask_pipeworx alternative, then covers core behavior, depth options, citation semantics, output details, and latency. Some emphatic negatives like 'NOT open-web search' and 'never invented' slightly repeat the same point, but nearly every sentence adds useful information.

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?

There is no output schema, so the description takes on the full burden of explaining return values—and it succeeds: findings packet contents, gaps[], contradictions[], hop field, citation_uri semantics, and latency are all disclosed. Authentication, free/paid tier requirements, and fallback behavior are covered. With only two parameters and full schema coverage, nothing essential 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 baseline is 3. The description adds valuable context beyond the schema: question should be broad/multi-part, 'thorough' requires a paid plan, and the depth parameter's behavior is explained in more operational detail (gap-recovery hop, follow-up pass, contradictions scan). This is genuinely helpful parameter-level guidance.

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?

States a specific verb and resource: 'Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources' and explicitly contrasts with open-web search. It distinguishes itself from a key sibling by saying 'For a single lookup use ask_pipeworx instead' and gives concrete example queries. An agent can confidently tell what deep_research is for versus the other research/query 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?

Gives explicit when-to-use guidance: 'Best for broad/multi-part questions over structured data' with two examples. Gives explicit exclusions: 'For a single lookup use ask_pipeworx instead' and 'If you are not signed in, use ask_pipeworx instead.' It also clarifies that 'thorough' depth requires a paid plan, which affects tool selection.

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