map_info

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

With no annotations provided, the description carries the full burden. It discloses the header-only behavior, the voxel-size derivation trap (cella/m vs cella/n), the ±5–15% accuracy caveat, and that anisotropy, cropping, and axis permutation are flagged. This is rich, honest behavioral detail.

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 well-structured and front-loaded with purpose. The subsequent sentences about safety and the derivation trap are all substantive and earn their place, making the length justified.

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 tool with an output schema, the description covers the core purpose, the safety model, a critical derivation trap, and the flags returned. There is no indication of missing needed context, and the output schema presumably covers return values.

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?

There is only one parameter, path, and the schema already describes it fully (file extensions and gzip support). The description adds no new parameter-level information, so the baseline 3 is appropriate given 100% schema coverage.

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 'Report an MRC/CCP4 map's geometry, above all its voxel size' — a specific verb and resource. It clearly differentiates this tool from siblings like load_map or density_view by focusing on extracting header-derived geometry without touching the map data or PyMOL.

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 says 'Reads only the 1024-byte header... PyMOL is never touched, and nothing goes over the network,' which provides clear context about when to use this lightweight reporting tool. It does not explicitly name alternatives or exclusions, but the usage context is strongly implied.

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