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 mentions 'Get' but does not specify if this is a read-only operation, what permissions are required, error handling, or response format. For a tool with no annotations, this leaves critical behavioral traits undefined, though it does not contradict any 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 a single, straightforward sentence that efficiently conveys the core action without unnecessary words. It is front-loaded and wastes no space, making it highly concise and well-structured for quick understanding.

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 (2 required parameters, no nested objects) and the presence of an output schema, the description is minimally adequate. However, with no annotations and low schema coverage, it lacks details on behavior and parameters. The output schema mitigates some gaps, but the description could be more informative for full context.

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, with parameters 'job_id' and 'approval_flow_id' documented only by title and type. The description does not add any semantic details, such as what these IDs represent, their format, or where to obtain them. With low schema coverage, the description fails to compensate, leaving parameters inadequately explained.

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 the tool 'Get a specific approval flow for a job,' which clearly indicates a retrieval action (get) on a resource (approval flow) with a scope (for a job). However, it does not differentiate from siblings like 'list_approvals_for_job' or 'list_pending_approvals,' which might offer similar or overlapping functionality, leaving the purpose somewhat vague in context.

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?

No guidance is provided on when to use this tool versus alternatives. The description lacks context on prerequisites, such as whether the job or approval flow must exist, or comparisons to sibling tools like 'list_approvals_for_job' for broader listings. This absence of usage instructions limits its effectiveness for an AI agent.

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