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 context beyond those annotations: account/plan requirements, parallel decomposition, explicit gaps[] for unanswered facets, never-invented evidence, resolvable citation_uri behavior, contradictions[] scanning, semantic excerpting, and expected latency. Nothing 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 densely informative: every sentence adds operational context an agent needs, from prerequisites to latency to output contents. It is front-loaded with the most critical constraint (account required and the alternative), then proceeds from core behavior to depth-specific details.

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 there is no output schema, the description fully explains the return payload: findings with evidence, confidence, source, fetched_at, citation_uri, gaps[], contradictions[], and hop field. It also covers routing, source scope, depth semantics, account tiers, and timing. No important missing context for selecting or invoking the tool is apparent.

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 schema already documents both parameters. The description adds value by explaining how depth affects behavior (gap recovery for standard, lead-chasing for thorough, contradictions[] for standard/thorough) and that broad/multi-part questions are appropriate. This goes beyond the baseline schema-only documentation.

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 verb and resource: it performs grounded multi-source research over Pipeworx's structured data sources, decomposing questions and routing to parallel tools. It clearly distinguishes itself from open-web search and explicitly contrasts with ask_pipeworx for single lookups, so an agent can differentiate it from 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?

The description gives explicit when-to-use guidance ('Best for broad/multi-part questions over structured data'), when-not-to-use guidance ('For a single lookup use ask_pipeworx instead'), and an account prerequisite with a fallback ('If you are not signed in, use ask_pipeworx instead'). It also clarifies paid-plan requirements for the thorough depth.

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