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

Annotations already mark the tool read-only, open-world, idempotent, and non-destructive. The description adds substantial behavioral detail beyond those annotations: account/pricing gating, parallel decomposition across 5,798 tools, gaps[] for unanswered facets, contradictions[] scanning, fetchable pipeworx:// citation URIs, semantically excerpted records, and latency expectations. Nothing in the description 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?

The description is long but information-dense and largely front-loaded with the account requirement, core purpose, and primary alternative before moving into behavioral details. Minor redundancy exists around 'thorough' being paid and repeated mentions of gaps/citations, which prevents a perfect score, but every major section earns its place for such a complex tool.

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?

There is no output schema, yet the description specifies the return envelope: verbatim evidence, confidence, source, fetched_at, pipeworx:// citations, gaps[], contradictions[], and hop fields. It also covers account requirements, latency, depth semantics, and when to prefer a sibling tool, giving an agent everything it needs to call and interpret the tool 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?

The input schema already documents both parameters at 100% coverage, but the description meaningfully extends that: it quantifies depth behavior (quick=3, standard=3, thorough=6), explains the gap-recovery hops and contradictions scan per depth, and explicitly states that the question parameter accepts natural-language broad/multi-part questions. This adds operational meaning beyond the schema's enum wording.

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 capability—grounded multi-source research over Pipeworx's 1,517 structured data sources—and explicitly contrasts it with open-web search and sibling tools by saying 'this is NOT open-web search.' It names the resource, the decomposition approach, and the output style ('findings packet'), so an agent can clearly distinguish it from ask_pipeworx and other research-related tools.

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 routing rules: if not signed in, use ask_pipeworx; for a single lookup, use ask_pipeworx; for breaking or current news, prefer ask_pipeworx; and for broad/multi-part structured-data questions, use deep_research. This is concrete when-to-use and when-not-to-use guidance that directly steers an agent to the correct sibling.

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