List Project Job Titles

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

The description adds valuable behavioral context beyond the annotations: project_id defaults to the value set by procore_set_config, pagination behavior with page and per_page, the response reports remaining pages, read-only side effects, and common error statuses (401, 403, 404). This enriches the agent's understanding beyond the structured annotations.

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 concise yet dense, with every sentence providing value: purpose, usage, pagination, read-only safety, error behavior, required parameters, and API reference. It is well-structured and front-loaded with the most important information.

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?

For a read-only list tool with no output schema, the description is complete: it specifies the return type (JSON array), pagination controls, default project_id, error handling, and the exact API endpoint. Combined with annotations, the description leaves no critical gaps for an agent to invoke 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?

Although the schema covers 100% of parameters, the description adds crucial semantic details: project_id defaults to the configured value when omitted, and page/per_page control pagination with the response indicating remaining pages. This goes beyond the schema's basic descriptions, providing meaningful usage guidance for each parameter.

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 function with a specific verb and resource: 'Return a distinct list of job titles for all contacts on a project.' It also explicitly distinguishes this from company-level job title tools by noting the project scope and the project_id parameter, making it easy to differentiate from siblings.

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 clear context on when to use the tool: 'Use this to discover project job titles or to look up the id of one before calling a tool that needs it.' It also explains the project_id default behavior. However, it does not explicitly mention when not to use it or name alternative tools (e.g., company-level job title listing), so it falls short of a 5.

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