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

Annotations already mark readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, and the description adds substantial behavioral context beyond that: parallel decomposition across 5,724 tools, latency expectations, depth tiers, gaps[] for unanswered facets, contradictions[] scans, hop fields, citation_uri fetchability, and semantic excerpting. It also states the tool 'never invented' findings. No contradiction with annotations is present.

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 every sentence carries operational value: auth requirements, usage gating, tool scope, decomposition behavior, output format, caveats, timing, and citation semantics. It front-loads the critical account requirement and the alternative tool. There is little fluff or tautology; the density is justified by the tool's complexity.

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?

Given the tool's complexity, the description is complete: it covers required account state, tier restrictions, when to use alternatives, expected latency, response structure, gaps/contradictions behavior, and citation resolvability. With no output schema, the description carries the full burden of explaining return values, and it does so thoroughly. An agent has enough context to select and invoke 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?

Schema coverage is 100%, so the baseline is 3, but the description adds meaningful semantics: it explains what depth values do behaviorally (gap recovery, lead-chasing, contradictions scan) and maps 'thorough' to a paid plan. It also clarifies that the question parameter may be broad/multi-part. This goes beyond the schema's enum descriptions without repeating them verbatim.

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 names a specific verb and resource: 'grounded multi-source research across Pipeworx's 1497 STRUCTURED data sources' in one call. It explicitly distinguishes itself from open-web search and from sibling tools like ask_pipeworx, so an agent can tell it apart without inspecting schemas. It also states the output type: a findings packet with evidence, confidence, source, fetched_at, and citations.

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 clear when-to-use guidance: 'best for broad/multi-part questions over structured data', and explicitly says to use ask_pipeworx for single lookups and for breaking/current-news topics. It also provides an account gate: if not signed in, use ask_pipeworx instead. This is model routing guidance, not just a capability statement.

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