py_eval

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

The description discloses major behavioral traits such as access to all IDA APIs and the blocking nature of long-running code. However, it does not explicitly mention potential side effects like database modification, which is a minor gap given no 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 concise with five sentences covering action, return, capabilities, and warning. It is well-structured and front-loaded, though the warning could be slightly more streamlined.

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 complexity of executing arbitrary code, the description covers the tool's purpose, output, capabilities, and the critical constraint of single-thread blocking. The mention of an alternative tool enhances completeness, though timeout limits are not addressed.

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 provides descriptions for both parameters (code and instance_id) with 100% coverage. The tool description adds no additional parameter-specific meaning beyond the schema's descriptions, meeting the baseline expectation.

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 executes Python code in the IDA context, specifying the return format and API access. It effectively communicates the core functionality without ambiguity.

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 explicitly warns against long-running operations and suggests using decompile_to_file as an alternative for batch decompilation. This provides clear guidance on when not to use the tool and recommends a specific alternative.

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