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

Annotations already mark the tool as read-only, open-world, idempotent, and non-destructive. The description adds substantial behavior beyond that: account and paid-plan requirements, parallel tool routing, findings packet structure, explicit gaps[], never-invented guarantees, fetchable citation URIs, semantic excerpting, contradictions[] on some depths, and expected latency.

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, with the most decision-relevant facts (account required, when to use ask_pipeworx) front-loaded. Some depth details repeat what the input schema already states, but the added latency, auth, citation, and excerpting details earn their place.

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?

This is a complex tool with no output schema, so the description carries the full burden of explaining return shape, failure behavior, citations, gaps, and depth semantics. It covers all of these thoroughly and even addresses real-world concerns like authentication, wait times, and citation resolvability.

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. The description adds meaningful depth-specific context — thorough requires a paid plan, quick is single-hop, standard adds gap recovery, and latency varies by depth — which enriches the enum semantics beyond the schema. It does not add much about the question parameter, but the schema already describes it well.

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: grounded multi-source research across 1517 structured data sources in one call. It clearly distinguishes itself from open-web search and from ask_pipeworx, which is the single-lookup alternative.

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 explicitly says to use ask_pipeworx when not signed in and for single lookups, and says deep_research is best for broad/multi-part questions over structured data. It gives concrete routing guidance and exclusions, so an agent can select correctly without guessing.

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