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

Even though annotations already declare readOnlyHint and idempotentHint, the description adds substantial behavioral context: parallel decomposition, returns findings with verbatim evidence/confidence/gaps, never invents data, returns contradictions for certain depths, semantically excerpts long records, and includes latency expectations. It also discloses the account/paid-plan requirement.

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 front-loads the account requirement and primary use case, then organizes limitations and behavioral details. Some repetition of 'use ask_pipeworx instead' could be trimmed, but nearly every sentence adds operationally relevant 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?

For a complex tool with no output schema, the description is remarkably complete: it explains what the findings packet contains, how citations are guaranteed fetchable, when gaps[] and contradictions[] appear, how large records are handled, authentication tiers, and expected latency. An agent has everything needed to select and invoke the tool 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?

Schema coverage is 100%, so the schema already documents both parameters. The description adds useful meaning beyond the schema by giving example multi-part questions, clarifying what 'standard' and 'thorough' do differently, and noting that 'thorough' requires a paid plan. However, it does not directly explain the 'quick' depth in the narrative, though the schema enum covers it.

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 uses a specific verb phrase and resource: 'Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources' in one call. It clearly distinguishes itself from open-web search and names ask_pipeworx as the sibling alternative for different use cases, 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?

The description gives explicit when-to-use guidance: it is 'Best for broad/multi-part questions over structured data.' It also states exclusions: 'For a single lookup use ask_pipeworx instead,' 'For BREAKING or colloquial current-news... prefer ask_pipeworx,' and 'If you are not signed in, use ask_pipeworx instead.' This is model-appropriate routing guidance.

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