where_used

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It communicates that this is a read-only query returning referencing nodes, but does not state whether references are direct or transitive, nor how results are ordered or limited.

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?

A single 10-word sentence that front-loads the verb and contains no filler. Every word earns its 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?

For a one-parameter read tool with an output schema covering return shape, the description is nearly complete. The remaining gaps — direct vs transitive reference semantics and what 'theorem-like nodes' includes — are modest but would help an agent set correct expectations.

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 0%, so the description must compensate. 'the given theorem' ties the sole required parameter (theorem_id) to the query semantics, but adds no detail on ID format or provenance (e.g., that IDs come from list_theorems or get_theorem).

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 uses a specific verb ('Return') and identifies the resource ('theorem-like nodes that reference the given theorem'), making the reverse-reference-lookup intent clear. It implicitly contrasts with the sibling get_dependencies (forward dependency lookup), though it never names a sibling and 'theorem-like' leaves the exact node types somewhat vague.

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 usage case is implied: given a theorem_id, find what references it. However, there is no explicit when-to-use guidance, no exclusions, and no mention of get_dependencies as the forward-direction alternative.

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