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

The description discloses a wealth of behavior beyond annotations: returns verbatim evidence + confidence + source + fetched_at + citations, reports gaps[] when unanswered, contradiction scanning, semantic excerpting rather than head-truncation, and explicit latency expectations (15-60s, thorough up to ~90s). It also clarifies that every citation is fetchable via a resolvable pipeworx:// URI. None of this is already in 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 each clause carries useful decision-weight — account requirement, depth-cost, use-cases, and what results carry. It front-loads those prerequisites and usage routing. Some redundancy (not being open-web search is repeated, ask_pipeworx alternative mentioned multiple times) makes it slightly less crisp than a tight-formatted spec, but given the tool's complexity it remains effective.

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?

Given the tool's complexity and lack of an output schema, the description nevertheless fully covers what an agent needs: return shape (findings packet with evidence, confidence, source, fetched_at, citation), gap handling, contradiction handling, latency, account/plan requirements, and when to fall back to a sibling. No critical behavior or requirement is left unstated.

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 covers both parameters at 100%, so description isn't needed for basic meaning, but it adds meaningful context: depth gets example facet counts ('quick=3', 'or 3=default', 'thorough=6') and explains what each depth does behaviorally (gap recovery hop, contradiction scan). The 'question' parameter is clarified by 'natural language, broad/multi-part fine.' This goes beyond the schema.

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 1541 structured data sources' in 'ONE call,' and explicitly differentiates itself from open-web search and from sibling ask_pipeworx. It explains precisely what the tool does (decompose question, route to 5,912 tools, return findings packet) and contrasts it with alternatives.

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 ('best for broad/multi-part questions over structured data') and when-not-to-use ('for a single lookup use ask_pipeworx', 'for BREAKING or colloquial CURRENT-NEWS... prefer ask_pipeworx'). Also names the alternative tool in multiple conditional contexts (signed-out, single lookup, news) and explains which depth does what for multi-step questions.

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