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

With annotations already marking it read-only, idempotent, and non-destructive, the description adds substantial behavioral context: it creates nothing, returns up to three available suggestions ranked best-first, and explains the format constraints. It also gives a concrete example of the output. This goes well beyond the structured safety hints.

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 front-loaded with purpose and output format, then lists inputs, then explains usage with an example. It is informative and mostly efficient, but the long inline enumeration of parameters is dense and could be more scannable. It earns its length overall but is not maximally crisp.

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 9 optional parameters, no schema descriptions, no output schema, and clear annotations, the description provides everything needed: what it returns, how suggestions are built, what each input represents, and how to use the result with create_short_link. An agent has no missing context 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 input schema has 0% description coverage, so the description carries the full burden. It maps all nine parameters to their real-world meaning (url = target address, title = link name, button = video button text, set_id = video/school campaign, code = bot funnel code, etc.) and provides an example of how inputs translate into suggestions. This fully compensates for the schema gap.

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: generating up to three available, readable link paths for a new short link, best first. It distinguishes itself from the sibling create_short_link by explicitly saying it creates nothing and by describing the output format (Latin, hyphens, max 40 chars). An agent can tell exactly what it does.

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?

It explicitly says to pass the chosen path to create_short_link and notes that without a path, create_short_link will choose the first suggestion itself. This gives clear when-to-use and how-to-use guidance relative to the alternative, leaving no inference needed.

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