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

Beyond the readOnlyHint and destructiveHint annotations, the description discloses topic-dependent output behavior: without a topic it returns an overview and topic list, with a topic it returns that section in full including 'mistakes that fail silently.' It also reveals data provenance—the values come from the same grammar the publisher validates against—adding meaningful trust context.

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 dense but well-structured: it front-loads the purpose, then platform scope, then usage timing, then behavior, then reliability. Examples like 'highlighting a phrase, a styled table, a collage' make the advanced-use case concrete without wasting space.

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?

Even without an output schema, the description tells the agent exactly what to expect for both call shapes (with and without topic), the non-Naver edge case, and the guarantee that returned syntax matches what publish accepts. Combined with the annotations, there is no obvious missing information for invoking the tool 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 already covers all three parameters at 100% coverage, so the baseline is met. The description adds extra meaning for the topic parameter by describing what happens with and without a topic, and clarifies platform behavior by noting that non-Naver platforms return not_supported rather than an error.

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 purpose: it provides the body-writing syntax for a channel that has its own markup, specifically Naver Blog. It distinguishes the tool from siblings by explicitly calling out that every other platform returns not_supported, making it unmistakably a lookup/reference tool rather than a publishing or mutation tool.

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 gives explicit call timing: 'Call this before writing a Naver Blog body for the first time, or whenever you want something the basics do not cover.' It also tells agents what to expect for unsupported platforms—not_supported is not an error to work around—which functions as clear when-not guidance.

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