recommend_mods

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

No annotations are provided, so the description carries the responsibility for behavior. It does convey that the tool produces recommendations and that dependency preservation is part of its logic, which suggests a non-mutating advisory operation. It does not explicitly state whether any changes are applied, but the verb 'suggest' weakly implies a read-only behavior.

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 entire description is a single focused sentence with no filler. It front-loads the core action and includes the key constraints compactly.

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 simple two-parameter advisory tool, the description covers the main purpose and constraint. However, since there is no output schema and no annotations, it does not describe the shape of the returned recommendations or confirm that no modifications are made, leaving some ambiguity.

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 helps by clarifying that 'world' can refer to a specific world or the whole instance, and that 'target count' maps to targetModCount. It does not name the parameters directly or add details like defaults, ranges, or the meaning of omission.

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 a specific action ('Suggest mods') and a clear objective ('to hit a target count and keep dependencies'), which makes the tool's purpose understandable. It does not explicitly contrast with siblings like analyze_mods or compare_mods, but the recommendation-focused intent is still clear.

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 implies when to use it: when the user wants to reach a target mod count while preserving dependencies, and for either a world or the whole instance. However, it provides no explicit guidance about when not to use it or which sibling alternative to prefer, so the agent must infer the boundary.

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