add_linkedin_language

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

With no annotations, the description carries the full behavioral burden, but it only says 'Add' without disclosing side effects, overwrite behavior, idempotency, or what a successful call returns. An agent cannot anticipate whether an existing proficiency is replaced, appended, or rejected.

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 one clean, front-loaded sentence with no filler or redundant restating of the tool name. It communicates the essential purpose immediately.

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?

Although the tool is simple and the schema is rich, the absence of annotations and the lack of behavioral or usage context leave an agent without enough information to know the consequences of the call or how to handle errors. The description is minimally viable but incomplete for robust tool selection and invocation.

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 already documents both parameters, including the proficiency enum, so the description adds no further semantic value. Since schema coverage is 100%, the baseline score of 3 is appropriate.

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 uses a specific verb ('Add') and identifies the exact resource ('a language to your LinkedIn profile'), so an agent can tell what operation is being exposed. It does not explicitly distinguish itself from sibling add_* tools, but the object differs clearly from them.

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?

There is no guidance about when this tool should be chosen over alternatives, such as add_linkedin_skill or the delete_linkedin_language sibling. The intended context must be inferred entirely from the tool name and description.

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