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

No annotations exist, so the description carries the full behavioral burden. It does disclose the read scope and one hard limitation (Instagram/Naver Place URLs fail), but says nothing about network failure modes, timeouts, permission/auth needs, or how long a fetch takes — meaningful omissions for a tool that scrapes a live external site.

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?

Two sentences, no filler. The extracted-field list is front-loaded so the agent knows the value proposition immediately, and the ordering constraint follows.

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, so the description correctly enumerates the returned fields and notes the migration hand-off context. What's missing is failure behavior — what the agent sees when the site is unreachable or partially parseable.

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?

With a single required parameter at 100% schema coverage, the schema already defines the `url` field. The description still adds real constraints the schema does not: the URL must point at an existing business site with home/menu structure, and Instagram/Naver Place links are rejected.

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 (Read) + resource (existing business website, home + menu pages) and enumerates what comes back: title, pages, phone/address/hours, brand colors & fonts, photo count. This is clearly distinguishable from gyeol_make_draft, which acts on the information rather than extracting it.

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?

"Use before gyeol_make_draft to show the user what will be migrated" gives an explicit sequencing rule against a named sibling, and "Instagram/Naver Place links are not readable" rules out an input class. The only gap is that no alternative is suggested for those unsupported sources, so the agent knows what not to try but not what to do instead.

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