add_project

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

No annotations are provided, so the description carries the burden. It discloses a key behavioral trait: strict locking to the authenticated account (/in/me). It also details the parameters with optionality and examples. However, it does not mention side effects (e.g., whether it overwrites existing projects), error handling, or rate limits. Given the output schema exists and the security notice is prominent, the description adds meaningful transparency beyond the basic action.

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 well-structured and front-loaded: purpose first, then security notice, then parameter breakdown. Every sentence adds value—no fluff. The parameter list is organized clearly with defaults and optionality, making it easy for an agent to parse.

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?

With 7 parameters, only 1 required, and an existing output schema, the description covers everything needed to call the tool correctly: it specifies the resource type, the scope (own profile), all parameter meanings and optionality, and the security constraint. The output schema handles return values, so no further description is necessary. The tool is actionable without ambiguities.

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 has 0% description coverage, so the description fully compensates by explaining every parameter: title, description, url, start_month, start_year, end_month, end_year. It provides examples (e.g., 'Argus Agent', 'January') and marks optionality. This gives an agent all the semantic meaning needed to populate arguments correctly.

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 action: 'Add a project to your own LinkedIn profile under Projects.' This specifies the verb (Add), resource (project), and precise location (own LinkedIn profile under Projects). It distinguishes this from sibling tools like add_education or add_experience by explicitly targeting the Projects section.

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 provides clear context: the tool is locked to the authenticated user's own profile, implying it is for adding projects to one's own profile rather than others. While it doesn't explicitly say when not to use it or name alternative tools, the 'Security Notice' and the phrase 'your own LinkedIn profile' give sufficient guidance for an agent to select it appropriately among similar add_* tools.

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