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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, and the description is consistent with them. Beyond annotations, it richly discloses behavior: parallel routing to 5,767 tools, the findings packet structure, explicit gaps[] with no invented answers, stable pipeworx:// citations, semantic excerpting rather than head-truncation, contradictions[] scanning, and expected latency ranges. This is far more than the annotations alone provide.

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 the tool is complex and nearly every sentence adds information. Critical operational constraints (account required, alternative tool) are front-loaded. There is minor redundancy: 'IN ONE call' appears twice, and the multi-step resolution point is re-emphasized. Overall it is well-structured with clear topical flow, though slightly verbose.

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 must convey the return shape — and it does: findings packet with verbatim evidence, confidence, source, fetched_at, stable citation_uri, gaps[], and contradictions[] where applicable. It also covers authentication tiers, latency, data-source scope, and how depth levels alter behavior. Nothing essential for invoking this tool correctly 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 value beyond the schema by explaining practical depth behavior: quick=3 facets, standard adds a gap-recovery hop and contradiction scan, thorough is paid and adds a follow-up iterative pass. It also reinforces that the question parameter is intended for broad natural-language queries, matching the schema but adding usage color.

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 1506 STRUCTURED data sources' in ONE call, and explicitly distinguishes itself from open-web search. It also differentiates from the sibling ask_pipeworx by scoping itself to broad/multi-part questions over structured data. This gives an agent clear, discriminating purpose information.

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 when-to-use guidance: 'Best for broad/multi-part questions over structured data' and 'For a single lookup use ask_pipeworx.' It also provides an authentication-based exclusion: if not signed in, use ask_pipeworx instead. Depth-selection guidance is also present, explaining what each depth tier adds.

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