Greenhouse MCP

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a list operation, implying read-only behavior, but doesn't mention pagination behavior (despite pagination parameters in schema), rate limits, authentication needs, or what 'all EEOC data' entails. For a tool with pagination parameters and no annotation coverage, this is insufficient.

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, efficient sentence with zero waste. It's front-loaded with the core purpose and appropriately sized for a list operation, though this conciseness comes at the cost of missing important details.

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 has an output schema (which helps), no annotations, and 3 parameters with 0% schema coverage, the description is incomplete. It doesn't explain pagination behavior, return format, or usage context. For a list tool with pagination parameters, this leaves significant gaps in understanding how to effectively use it.

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 for undocumented parameters. It mentions 'all EEOC data' but provides no information about the three pagination parameters (per_page, page, paginate) or their semantics. The description adds no value beyond what's inferred from the tool name, failing to address the parameter gap.

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 ('List') and resource ('all EEOC data collected from applications'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_eeoc_for_application' which appears to retrieve EEOC data for a specific application, so it misses full sibling distinction.

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 like 'get_eeoc_for_application' or other list tools. It lacks context about prerequisites, appropriate scenarios, or exclusions, leaving the agent with minimal usage direction.

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