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

Beyond the readOnlyHint/openWorldHint/idempotentHint annotations, the description discloses account requirements, latency ranges, the exact findings-packet shape, gaps[] never being invented, contradictions behavior by depth tier, and the fetchability condition for citation URIs. It also explains semantic excerpting rather than head-truncation. No annotation contradiction exists.

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 information-dense and front-loaded with the account requirement and fallback tool, which is helpful. However, it is a long wall of text with parenthetical asides and some redundancy around citations (findings packet components vs. citation_uri semantics). It earns its length for a complex tool, but is not maximally concise.

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?

With no output schema, the description carries the return-value burden and handles it thoroughly: it enumerates evidence, confidence, source, fetched_at, citation URIs, gaps[], contradictions[], and citation fetchability. It also covers auth, alternatives, depth behavior, and expected latency, so an agent has enough context to 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 description coverage is 100%, so the baseline is 3; the description adds meaningful depth-specific behavior (standard adds gap recovery, thorough chases leads and runs a contradiction scan) and latency expectations. It also clarifies that the question can be broad and multi-part, though the schema already documents that adequately.

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 capability: grounded multi-source research over 1,517 structured data sources, with decomposition into facets and parallel routing. It clearly distinguishes itself from open-web search and from ask_pipeworx, which is named as the single-lookup alternative. Examples of suitable questions reinforce the intended use.

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 states that deep_research is best for broad/multi-part questions over structured data. It also gives practical selection guidance for depth tiers, including that 'thorough' requires a paid plan.

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