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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive, and the description goes well beyond that: account/paywall caveats, parallel decomposition into 5,798 tools, gap[] behavior ('never invented'), contradictions[] on certain depths, hop semantics, citation_uri fetchability guarantees, semantic excerpting rather than head-truncation, and realistic latency expectations. This is rich behavioral disclosure that materially affects invocation decisions and result interpretation.

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 every sentence carries actionable information: requirements, alternatives, core mechanism, output structure, failure behavior, latency. It front-loads the critical gate (account required, use ask_pipeworx otherwise) before diving into mechanics. For a tool this complex, the density is justified and there is little fluff or repetition.

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?

Despite having no output schema, the description fully explains what the agent will receive: findings packet with verbatim evidence, confidence, source, fetched_at, pipeworx:// citation, gaps[], contradictions[], and hop field. It also covers prerequisites, pricing tiers, latency, and sibling alternatives. Nothing an agent needs to safely invoke this tool or interpret its results 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 baseline is 3, but the description adds significant value: it explains the practical behavioral differences between depth values (quick=3 single hop, standard=3 with gap recovery and contradictions scan, thorough=6 paid with iterative chase), and it clarifies that 'question' is free-form, natural language, and explicitly supports broad/multi-part input. This goes beyond the enum labels and parameter names.

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 1517 STRUCTURED data sources' in one call, and explicitly distinguishes itself from open-web search and from ask_pipeworx. It also enumerates concrete use cases and example questions, so an agent can immediately understand what this tool does and how it differs from siblings.

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 explicit when-not-to-use recommendations: 'For a single lookup use ask_pipeworx instead' and 'If you are not signed in, use ask_pipeworx', plus a current-news caveat. It even names the alternative and the reasoning, leaving no ambiguity for tool selection.

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