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

Annotations already cover the read-only, closed-world safety profile. The description adds genuinely non-obvious behavior: the model and parameters are fixed server-side, responses are optimized for speed, and each call costs a base 100 points with usage-based charging if higher — information an agent cannot get from annotations or schema.

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 core capability and the 100k limit are front-loaded, which is good, but the English and Korean sentences are near-duplicates and the 100-point cost is stated twice (once inline, once in the bracketed tag). Bilingual mirroring roughly doubles the length without adding information.

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 no output schema, the description covers input limits, cost, and fixed-model behavior. It never says what the response looks like (the polished string, any metadata), which is the one remaining gap.

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?

Only one parameter with 100% schema coverage, so the baseline is 4. The 100,000-character limit appears in both the description and the schema field, so the description adds no new parameter-level meaning.

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 — polishing text by fixing grammar, spelling, awkward phrasing and sentence order while preserving meaning. That is clearly distinct from text_summary (which condenses) and llm_chat (general conversation), though it never names those siblings explicitly.

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?

Usage is only implied: the tool is for correcting/proofreading a text. There is no explicit when-to-use vs. when-not-to-use, and no guidance on preferring text_summary or llm_chat for adjacent needs.

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