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TylerIlunga

Procore MCP Server

Create Project Observation Type

create_project_observation_type

Create a new observation type for a Procore project. Specify name, category, or parent to categorize observations.

Instructions

Creates a Project Observation Type with the specified name/parent_id. Use this to create a new Observations in Procore. Creates a new Observations and returns the created object on success (HTTP 201). Required parameters: project_id. Procore API: Project Management > Observations. Endpoint: POST /rest/v1.0/projects/{project_id}/observation_types

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYesURL path parameter — unique identifier for the project.
nameNoJSON request body field — name to be used for Observations created from this type.
categoryNoJSON request body field — category to be used for Observations created from this type.
observations_category_idNoJSON request body field — observations category id to be used for Observations created from this type.
activeNoJSON request body field — active or no.
parent_idNoJSON request body field — unique identifier of the parent
Behavior3/5

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

Annotations indicate a write operation (readOnlyHint false) and non-destructive (destructiveHint false). The description adds that it returns HTTP 201 and the created object, but does not disclose authorization requirements, rate limits, or potential side effects. It does not contradict annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise (two sentences plus metadata) and front-loaded with the main action. It includes useful API details (category, endpoint). No wasted words, though it could be slightly more structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description mentions the returned object and HTTP 201, but lacks details on required parameters beyond project_id, validation rules (e.g., uniqueness of name), or what the response object contains. Adequate but incomplete for a create operation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema has 100% description coverage. The description mentions only name and parent_id as key parameters, ignoring category, observations_category_id, and active. While schema already describes each parameter, the description adds minimal extra meaning beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that the tool creates a Project Observation Type, specifying key parameters like name and parent_id. It differentiates from other create tools by the resource name, though it slightly confuses 'Observation Type' with 'Observations'. Overall, the purpose is clear.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides minimal guidance on when to use this tool versus alternatives. It says 'Use this to create a new Observations in Procore' but does not mention exclusions or comparable tools like create_observation_item. No explicit when-not-to-use or alternative references.

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

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