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

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds valuable behavioral context beyond the annotations: it discloses what the tool returns (API signatures and usage examples) and its intended downstream purpose. For a lookup tool with no output schema, this is meaningful disclosure, though it stops short of describing result breadth or limits.

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?

Two sentences, front-loaded with the verb and resource, followed by illustrative examples. Only minor redundancy in "IDA Pro ida-domain Python API." Every element serves the reader, and the most important information leads.

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 single-parameter, read-only lookup tool with no output schema, the description adequately covers what the tool does, the query style, and what is returned. The gap is the absence of explicit guidance on using it before execute_python, but otherwise the definition is complete for its complexity.

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 the query parameter is already documented, establishing a baseline of 3. The description goes beyond the schema by illustrating the expected query content with five concrete examples spanning both task descriptions and API names, which clarifies how vague or specific the input should be.

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?

States a specific verb ("look up") and resource (the IDA Pro ida-domain Python API), and the examples ("decompile function", "xrefs to address", "list strings") make clear this is a reference/documentation tool, not an analysis tool. An agent can distinguish it from analysis siblings like decompile or execute_python without opening a 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 "by task or name" phrasing plus concrete example queries conveys how to phrase a lookup, and the closing clause ties it to "IDA analysis via execute_python," implying this is the discovery step before writing Python. However, there is no explicit when-to-use/when-not guidance or named alternative, so usage is only implied.

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