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

Annotations only declare readOnly/idempotent/non-destructive/openWorld; the description adds far more: auth and paywall requirements, 15–60s (up to ~90s) latency, gaps[] instead of invention, contradictions[] only on standard/thorough, semantic excerpting rather than head-truncation, and that citation URIs are only emitted when resolvable via resources/read. No contradictions with 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?

Dense but well ordered: auth gate first, then purpose, then mechanism, then alternatives, then depth/behavioral notes. Every sentence carries signal, though the parenthetical stacking ('(gap recovery)', '(paid; adds a full iterative hop...)') and ALL-CAPS emphasis make it heavier than necessary.

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?

No output schema exists, and the description compensates by describing the return packet precisely: per-finding verbatim evidence, confidence, source, fetched_at, pipeworx:// citation, hop field, plus top-level gaps[] and contradictions[]. Combined with latency and auth details, an agent has everything needed to decide and call 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 baseline is 3, but the description adds value beyond the schema by tying depth to observable behavior and cost: thorough requires a paid plan, standard re-angles unanswered gaps, thorough chases first-pass leads, and each depth maps to a latency envelope. The seven alias parameters are not discussed, but the schema already documents them as aliases.

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 with explicit scope: 'grounded multi-source research across 1,861 STRUCTURED data sources... in ONE call', plus a working mechanism (facet decomposition, parallel routing across 7,163 tools). It explicitly disclaims a common misread ('this is NOT open-web search'), which cleanly separates it from web-search 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?

Gives use cases with examples ('compare X and Y's regulatory + financial exposure'), a size-based discriminator ('For a single lookup use ask_pipeworx'), and a topical exclusion ('for BREAKING or colloquial CURRENT-NEWS... prefer ask_pipeworx... deep_research returns mostly empty gaps[]'). It also states the account/tier precondition and routes unsigned users elsewhere.

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