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

Annotations already mark readOnly/openWorld/idempotent, and the description adds valuable behavioral context beyond them: explicit gaps[] for unanswered facets, contradictions[] scans for standard/thorough depths, 'never invented' evidence, structured-data-only scope, large-record semantic excerpting, latency expectations, and the paid threshold for thorough. There is no contradiction with 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 wordy and repetitive: the findings-packet contents are described twice, 'never invented' appears more than once, and 'This operation only reads data; no writes' duplicates the annotations. It also front-loads account/signup details before the core purpose, which makes the structure less scannable than it could be.

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 takes on the burden of explaining return semantics, and it does so thoroughly: verbatim evidence, confidence, source, fetched_at, stable pipeworx:// citations, gaps[], contradictions[], latency, and coverage limits. It also covers auth/tier requirements and sibling-alternative routing, so an agent has enough to invoke it correctly in context.

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 description carries little unique parameter burden. It mostly restates the depth schema's behavior, though it adds useful color such as example research questions, latency ranges per depth, and the paid-plan constraint for thorough. This matches the baseline 3 for high schema coverage.

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 ('Decomposes your question into focused facets, routes each to the right one of 5,908 tools IN PARALLEL') over a clearly bounded resource ('1540 STRUCTURED data sources', 'NOT open-web search'). It also distinguishes itself from siblings by scope and by explicitly saying 'For a single lookup use ask_pipeworx instead.' An agent can tell what this tool does and what it is not.

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'), explicit when-not-to ('For a single lookup use ask_pipeworx instead'), and names concrete alternatives with usage conditions, including compare_entities, entity_profile, state_summary, search_within, and validate_claim. Auth and tier prerequisites are also stated up front ('ACCOUNT REQUIRED... if you are not signed in, use ask_pipeworx instead').

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