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

Annotations already declare readOnlyHint/openWorldHint/idempotentHint, but the description adds substantial behavior beyond them: auth prerequisites and paid-tier requirement for depth:'thorough', the parallel facet-routing execution model, gap recovery hops for standard/thorough, contradictions[] scanning, the guarantee that citations are always fetchable (never invented), semantic excerpting of large records, and concrete latency expectations (15-60s, ~90s for thorough). This fully discloses the tool's operational characteristics.

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 (~280 words) but nearly every sentence earns its place for a tool with this much behavioral complexity. It front-loads the most decision-critical information (account requirement, fallback tool) before the mechanism details. Minor structural weakness: it's one dense wall of text with slight redundancy — gaps[] is described twice — but no filler sentences exist.

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 no output schema, the description carries the full burden of documenting return values and does so thoroughly: findings packet contents (verbatim evidence, confidence, source, fetched_at, hop, citation_uri), the gaps[] mechanism, and the contradictions[] field. Combined with auth, latency, alternatives, and parameter semantics, nothing an agent needs to correctly select and invoke this tool is missing.

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 covers 100% of parameters with descriptions, so baseline is 3. The description adds value beyond the schema by tying depth choices to real-world consequences — 'thorough' requires a paid plan, standard adds a gap-recovery hop plus contradictions scan, and latency scales with depth. It also clarifies that 'question' can be broad/multi-part because decomposition is the point, reinforcing the schema's natural-language guidance.

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 and resource: 'Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources... in ONE call.' It explicitly differentiates from siblings with 'this is NOT open-web search' and names ask_pipeworx as the alternative for single lookups and unsigned-in users. An agent can distinguish this from every sibling tool without opening the schema.

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 conditions: 'Best for broad/multi-part questions over structured data' with concrete example queries, plus explicit exclusions: 'For a single lookup use ask_pipeworx' and 'If you are not signed in, use ask_pipeworx instead — it works on every tier.' The alternative tool is named with the exact condition that selects it.

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