The cross-reference corpus in aggregate

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the read-only nature is covered. The description adds useful behavioral context: the three invocation modes and the kind of result each produces (totals, hubs, book-to-book pairs, rows, rank/vote weight). It does not address edge cases like mutually exclusive parameters, but that is a minor gap.

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 three sentences with no filler. The first sentence establishes the tool's conceptual scope, the second explains the three invocation modes, and the third provides the sibling routing. It is slightly verbose in phrasing ('Questions about the SHAPE...') but remains compact and well-organized.

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?

The tool has a rich output schema, all three parameters are described in the schema, and the description covers the no-argument, book, and osis cases plus the alternative tool to use. Nothing needed for correct selection is missing: an agent knows what to expect, what parameters to pass, and which sibling to prefer.

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 a baseline of 3 applies. The description goes beyond the schema by linking each parameter to a specific behavior: 'book' produces incoming/outgoing rows, 'osis' produces rank and vote weight, and no argument returns totals and top-ranked items. This adds real selection value.

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, resource, and scope: it returns aggregate shape-of-the-corpus analytics for cross-references rather than per-verse references. It distinguishes itself from find_cross_references, which retrieves actual references, so an agent can select it without inspecting the schema.

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 conditions for each invocation mode: no argument for global totals/hubs, book for one book's rows, osis for a chapter's rank/vote weight. It names the sibling find_cross_references as the alternative and states the exact criterion for when to use it instead (getting actual references for a passage).

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