Greenhouse MCP

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states 'Get' which implies a read operation, but doesn't specify if it requires authentication, returns errors for invalid IDs, includes rate limits, or what the output contains (though an output schema exists). For a read tool with zero annotation coverage, this is a significant gap in behavioral context.

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 a single, clear sentence with no wasted words. It front-loads the core action ('Get a single job post') and specifies the key constraint ('by ID'), making it efficiently structured and easy 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?

Given the tool's low complexity (single parameter, read operation) and the presence of an output schema (which handles return values), the description is reasonably complete. It covers the basic purpose and parameter use. However, it lacks behavioral details like error handling or authentication needs, which are important even with an output schema, preventing a perfect score.

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 description adds meaning by specifying that the parameter 'job_post_id' is used to retrieve 'a single job post', clarifying its purpose beyond the schema's basic type (integer). With 0% schema description coverage and only one parameter, this compensation is effective. However, it doesn't detail ID format or validation rules, keeping it from a perfect score.

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 verb 'Get' and the resource 'a single job post by ID', making the purpose specific and understandable. It distinguishes this from sibling tools like 'list_job_posts' or 'get_job_post_for_job' by specifying retrieval of a single item via ID. However, it doesn't explicitly differentiate from other 'get_' tools like 'get_job' or 'get_job_opening', which slightly limits sibling differentiation.

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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a valid job_post_id), exclusions, or comparisons to similar tools like 'get_job' or 'list_job_posts'. This lack of context leaves the agent to infer usage from the tool name alone.

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