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

Adds substantial context beyond the readOnly/openWorld/idempotent annotations: account requirement, paid tier for thorough, latency expectations (15-60s, up to ~90s), gap[] semantics with never-invented guarantee, contradictions[] flagging, per-finding citation_uri fetchability guarantee, and semantic excerpting behavior. No contradiction with annotations; openWorldHint aligns with multi-source research.

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?

Dense but every sentence earns its place given the tool's complexity; critical constraints (account, paid tier, alternative routing) are front-loaded. Slightly above a 4 because the single-paragraph wall of text could be better sectioned, but there is zero filler.

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-format burden and meets it: findings packet contents (verbatim evidence, confidence, source, fetched_at, pipeworx:// citation), gaps[] for unanswered facets, and contradictions[] for standard/thorough. Auth, latency, depth semantics, and when-not-to-use are all covered.

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, but the description adds real semantic value beyond the schema: it explains what each depth enum value does (quick=3 facets single hop, standard=3 with gap-recovery hop + contradictions scan, thorough=6 paid iterative hop) and gives example question phrasings for the question parameter.

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?

States a specific verb+resource: grounded multi-source research across Pipeworx's 1517 structured data sources in one call. Explicitly distinguishes itself from siblings ('this is NOT open-web search', 'For a single lookup use ask_pipeworx instead'), so an agent can tell it 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?

Gives explicit when-to-use ('broad/multi-part questions over structured data') with concrete examples, and names the alternative with the condition that selects it ('If you are not signed in, use ask_pipeworx instead; For a single lookup use ask_pipeworx instead'). Nothing is left to inference.

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