recommend_supercell

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

No annotations are provided, so the description carries the full burden. It discloses the calculation logic (axis length rule and charge-dependent method choice), which is useful. However, it does not mention potential side effects, error handling, or what happens if the CIF has no charges or invalid data, leaving the agent with incomplete behavioral understanding.

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 and front-loaded with the main action. Two sentences convey the core purpose and additional logic without unnecessary words or repetition.

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?

There is no output schema and no returned value description. The description states what the tool recommends but not the structure of the output (e.g., a dictionary with supercell and charge_method). It also lacks edge-case behavior, making it incomplete for an agent to invoke and process results confidently.

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 description coverage is 0%, so the description must compensate. It does add semantic meaning to both parameters: 'cutoff_A' is tied to the minimum-image rule, and 'cif_path' is implied to be a CIF file used to detect charges. However, it does not explicitly describe the expected format of 'cif_path' or units of 'cutoff_A' beyond the variable name, so it only partially compensates.

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's function: recommending an integer supercell (nx, ny, nz) with a specific rule (minimum-image 2×cutoff_A) and also recommending a ChargeMethod. It uses a specific verb ('recommend') and resources ('supercell', 'ChargeMethod'), and distinguishes it from sibling recommendation tools like 'recommend_forcefield'.

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 clear context for when to use the tool: when constructing a supercell for RASPA2 simulations with a minimum-image rule, and when determining a charge method based on CIF charges. However, it does not explicitly mention alternatives or exclusions, so it stops short of a 5.

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