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

Annotations already carry readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, and the description adds rich context beyond them: account/pricing gate (thorough needs a paid plan), latency expectations (15-60s, thorough up to ~90s), the never-invents guarantee via explicit gaps[], the contradictions[] scan for disagreeing findings, the hop field and resolvable citation_uri semantics, and semantic excerpting of large records. No contradiction with annotations exists.

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 dense and mostly earns its place, and it front-loads the most critical gate (account requirement) before anything else. However, it is a single sprawling wall of text with parentheticals piling up, and it carries redundancy — contradictions[] is mentioned both in the description and the schema's depth parameter, and the ask_pipeworx alternative is stated twice for different reasons. It would benefit from paragraph or bullet structuring without adding length.

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 burden is on the description to explain return values — and it does so thoroughly: findings packet with verbatim evidence, confidence, source, fetched_at, stable pipeworx:// citation, gaps[], contradictions[], hop, and citation_uri. It also covers auth requirements, cost tier, latency, data scope, exclusions, and sibling routing. An agent has everything needed to call it 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 description coverage is 100%, so the baseline is 3; the description adds meaningful extra semantics on top, notably that depth:'thorough' is paid, that standard adds a gap-recovery hop plus contradictions[], and that thorough chases leads from the first pass with a longer latency. The schema already documents the enum values well, so the description's added value is modest but real.

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 clear, specific verb+resource: 'Grounded multi-source research across Pipeworx's 1500 STRUCTURED data sources' in ONE call, and draws an explicit line against open-web search ('this is NOT open-web search'). It also names the sibling it is not — 'For a single lookup use ask_pipeworx' — so an agent can distinguish it from the ask_pipeworx family without ambiguity.

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?

Usage routing is explicit and multi-branched: if not signed in, use ask_pipeworx; for a single lookup, use ask_pipeworx; for breaking/current-event topics, prefer ask_pipeworx; and deep_research is reserved for 'broad/multi-part questions over structured data'. These are concrete conditions with named alternatives, leaving nothing to inference.

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