Greenhouse MCP

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

No annotations are provided, so the description carries full burden. It discloses key behavioral traits: sequential processing, rate-limit delays to avoid Greenhouse's 50 req/10s limit, and that it returns a summary of successes and failures. This covers execution method, constraints, and output format adequately for a bulk operation.

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 front-loaded with the core purpose, followed by usage guidelines, parameter explanation, and behavioral details. Every sentence adds value with zero waste, and it's structured logically from general to specific.

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 complexity (bulk mutation with rate limits), no annotations, 0% schema coverage, but with an output schema, the description is complete. It covers purpose, usage, parameters, behavior, and output summary, providing all necessary context for safe and effective use.

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?

Schema description coverage is 0%, so the description must compensate. It explains all three parameters: 'application_ids' (list of IDs to reject), 'rejection_reason_id' (optional, from list_rejection_reasons), and 'rejection_email' (optional boolean to send email). This adds meaningful context beyond the bare schema, though it doesn't detail parameter formats or constraints.

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 ('reject') and resource ('multiple applications') with specific scope ('in one call'), distinguishing it from the sibling 'reject_application' which handles single rejections. The purpose is specific and unambiguous.

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?

Explicit guidance is provided: use for 'pipeline hygiene' with 'stale candidates after reviewing the output of stale_applications.' It names a specific sibling tool ('stale_applications') as a precursor and provides a concrete example scenario ('bulk-reject 30 stale candidates').

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