preview_mod

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 declares read-only scanning, no AI API calls, no token consumption, and no file writes. It also states the return content is a preview summary JSON, giving a strong safety and behavior profile.

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?

Front-loaded with the key purpose and scope, then supporting details and Args/Returns. Slight redundancy between '零成本' and '不消耗 token' keeps it from being maximally tight.

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 an output schema exists, the description need not detail return values, and it still summarizes them. It covers the single input, safety behavior, and usage context, leaving no major gaps for an agent to call it correctly.

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 has one parameter with 0% description coverage, but the description defines jar_path as the absolute path to a mod jar file. This compensates adequately, though no further path constraints are given.

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 and resource: preview a single mod's localization scope, listing language files, entry counts, and estimated tokens. It is clear but does not explicitly name or differentiate itself from siblings such as dry_run_mod, so sibling differentiation remains implicit.

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?

Provides a clear context: use before actual translation to assess workload and cost. It also states what it does not do (no AI API, no token use, no file writes), but it does not explicitly say when to choose it over dry_run_mod or translate_mod.

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