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

Even with read-only/open-world/idempotent annotations, the description adds substantial behavioral context: account and paid-tier requirements, which depth modes return contradictions[], guaranteed fetchable citations via pipeworx:// URIs, semantic excerpting rather than head-truncation, and expected latency. It also discloses that gaps are reported as gaps[] and never invented. No contradiction with 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 the tool has a complex behavior and every section adds a distinct detail: access, scope, alternatives, output contract, depth variations, citation semantics, excerpting, and latency. It is front-loaded with the account requirement and alternative first. It could be trimmed into clearer short sections, but it is not padded.

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 fully specifies the return contract: findings packet fields, gaps[], contradictions[], hop field, citation_uri existence condition, and latency. Combined with the rich parameter schema, an agent has everything needed to select the tool and invoke it 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, including depth mode behavior and the fact that question accepts broad natural-language queries. The description reinforces those semantics (e.g., second-hop iteration, multi-step resolution) but adds little new parameter-level meaning beyond what the schema provides, so the high-coverage baseline of 3 is appropriate.

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 action — grounded multi-source research over 1,517 structured data sources in a single call — and explicitly distinguishes itself from open-web search. It also names the sibling/alternative ask_pipeworx and the conditions that route to it, so an agent can tell deep_research apart without ambiguity.

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?

It gives explicit when-to-use guidance ('Best for broad/multi-part questions over structured data') and explicit when-not-to-use guidance ('For a single lookup use ask_pipeworx instead'). It also adds the access condition: if not signed in, use ask_pipeworx. This is stronger than most sibling-routing descriptions.

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