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 states 'Get EEOC data' but doesn't disclose behavioral traits such as whether this is a read-only operation, what permissions are required, if it returns structured data or a file, error handling, or rate limits. For a data retrieval tool with zero annotation coverage, this is a significant gap in transparency.

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's front-loaded with the core action and resource, making it easy to parse quickly. Every part of the sentence contributes directly to understanding the tool's purpose.

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 (1 parameter) and the presence of an output schema (which likely describes the EEOC data structure), the description is somewhat complete for basic understanding. However, with no annotations and 0% schema description coverage, it lacks crucial context like behavioral traits and parameter details, making it inadequate for fully informed use without external knowledge.

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 mentions 'for a specific application', which aligns with the 'application_id' parameter in the schema. However, schema description coverage is 0%, so the schema provides no details about the parameter. The description adds minimal semantic context (it's for an application) but doesn't explain what an 'application_id' is, its format, or where to obtain it, leaving the parameter poorly documented.

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 ('Get') and the resource ('EEOC data submitted for a specific application'), making the purpose understandable. It distinguishes from sibling tools like 'list_eeoc' (which likely lists EEOC data broadly) by specifying retrieval for a single application. However, it doesn't explicitly contrast with other data-fetching tools like 'get_application', leaving minor ambiguity.

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 an existing application ID), exclusions (e.g., not for bulk EEOC data), or direct comparisons to siblings like 'list_eeoc' or 'get_application'. Usage is implied through the parameter name but not explicitly stated.

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