Procore MCP Server

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 only states the HTTP method (POST) and endpoint, but fails to describe critical traits: it's a write operation (implied by 'Create'), potential side effects (e.g., database insertion), required permissions, rate limits, or error conditions. This is inadequate for a mutation tool with zero annotation coverage.

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 brief and front-loaded with the core action ('Create Observation Item'), followed by category and endpoint details. It wastes no words, though it could be more informative. The structure is clear but under-specified, not overly verbose.

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 complexity (5 parameters, nested objects, no output schema, and no annotations), the description is insufficient. It lacks details on the observation item's purpose, creation workflow, expected outputs, or error handling. For a mutation tool in a project management context, this leaves significant gaps for an agent to operate effectively.

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 100%, meaning all parameters are documented in the schema itself (e.g., 'project_id' and 'observation' are required). The description adds no additional semantic context about parameters, such as the structure of the 'observation' object or how 'run_configurable_validations' affects the process. Baseline 3 is appropriate since the schema does the heavy lifting.

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 action ('Create Observation Item') and provides a category hint ('Project Management/Observations'), which clarifies the general purpose. However, it lacks specificity about what an 'Observation Item' entails (e.g., a safety issue, quality check) and does not differentiate from sibling tools like 'create_observation_item_response_log' or 'create_observation_type', making it 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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites (e.g., needing an existing observation category), exclusions, or related tools like 'update_observation_item' or 'list_observation_items', leaving the agent with no usage context.

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