get_theorem

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

With no annotations, the description carries the burden. It does disclose the response nature (full text and metadata for one node), but it does not mention error behavior, identifier requirements, side effects, or how the node is located. For a simple getter, this is modest but incomplete coverage.

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 a single, front-loaded sentence with no filler. Every word contributes to the core contract, making it easy to parse and remember.

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 getter with no output schema and no annotations, the description conveys the essential operation and return content. It leaves the agent to infer where to obtain a theorem_id (likely from list_theorems) and lacks error-case handling, but the simplicity of the tool keeps it mostly complete.

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 0% and the description adds no explanation of theorem_id beyond its name. It does not specify where the ID comes from, its format, or how it relates to other tools. The parameter name is suggestive, but the description itself provides almost no semantic value beyond the schema.

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 clear verb (Return) and resource (full text and metadata for one theorem-like node), which distinguishes it from list_theorems and dependency/usage tools. The phrase 'theorem-like node' is slightly vague, but the intent is unambiguous.

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?

No guidance is given for when to choose this tool over siblings like list_theorems or get_dependencies. The agent must infer the appropriate context from the tool name and the required theorem_id. There is no explicit statement of prerequisites, alternatives, or exclusions.

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