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

Annotations already cover the safety profile (readOnly, non-destructive, idempotent, open-world), and the description goes far beyond: account/tier requirements, parallel routing across 5,743 tools, findings packet structure with gaps[] and 'never invented' guardrail, hop/contradictions[] semantics per depth, resolvable citation_uri guarantee, semantic excerpting, and 15-90s latency expectations. No mention 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?

Every sentence earns its place — auth, purpose, alternatives, iteration semantics, return contract, and latency are all substantive with zero filler. It is dense and somewhat long, with some depth semantics repeating the schema's enum descriptions, and minor formatting quirks (odd capitalization in 'BREAKING'/'CURRENT-NEWS') slightly mar readability.

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?

With no output schema, the description carries the return-contract burden and does so thoroughly: per-finding fields (verbatim evidence, confidence, source, fetched_at, pipeworx:// citation), gaps[], contradictions[], hop field, and citation_uri resolvability. Combined with auth, latency, and depth guidance, an agent has everything needed to invoke the tool and interpret results 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% and the depth enum already carries detailed facet/hop descriptions, so the baseline is 3. The description adds genuine value by tying depth to operational consequences (paid tier, latency range, lead-chasing behavior) and confirming question accepts broad multi-part natural language. It enriches depth meaningfully but adds little for question beyond what the schema already states.

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+resource: grounded multi-source research across Pipeworx's 1500 structured data sources in ONE call, and explicitly disambiguates itself ('this is NOT open-web search'). It further distinguishes from the nearest sibling by naming ask_pipeworx with concrete conditions for preferring it, so an agent can discriminate tools 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?

Explicit when-to-use ('Best for broad/multi-part questions over structured data') and when-not-to-use conditions are given: single lookups, breaking/current-news topics, and unsigned-in users should route to ask_pipeworx instead. The description even grounds the exclusion in a behavioral consequence ('deep_research returns mostly empty gaps[] when the topic isn't in the structured catalog').

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