lean_run_code

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

Annotations already declare the tool as read-only and idempotent. The description adds that it returns diagnostics and requires imports, which provides some behavioral context beyond annotations but does not detail error handling or output format.

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 two sentences, with the first stating the core purpose and the second providing a critical constraint. No extraneous information—every sentence 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?

Given the simple tool with one parameter, an output schema, and clear annotations, the description is complete. It covers what the tool does, what it returns (diagnostics), and a prerequisite (imports). No gaps.

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?

The schema already describes the 'code' parameter as 'Self-contained Lean code with imports' (100% coverage). The description reiterates the import requirement but adds no new semantic detail beyond that.

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 clearly states the tool runs a code snippet and returns diagnostics. While it distinguishes from siblings like lean_build or lean_verify by focusing on execution and diagnostics, it does not explicitly contrast with them.

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 provides one key usage requirement ('Must include all imports'), but lacks guidance on when to use this tool versus alternatives like lean_verify or lean_completions. No explicit context for ideal use cases.

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