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TylerIlunga

Procore MCP Server

Create Punch Item

create_punch_item

Create a new punch list record in a Procore project. Provide the project ID and punch item details; optionally upload images and attachments as multipart/form-data.

Instructions

Create a new Punch Item in a Project. #### Uploading images To upload images you must upload the entire payload as multipart/form-data content-type and specify each parameter as form-data together with punch_item[images][] as files. Use this to create a new Punch List records in Procore. Creates a new Punch List records and returns the created object on success (HTTP 201). Required parameters: project_id, punch_item. Procore API (v1.1): Project Management > Punch List. Endpoint: POST /rest/v1.1/punch_items

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
run_configurable_validationsNoQuery string parameter — if true, validations are run for the corresponding Configurable Field Set.
project_idYesJSON request body field — project ID to which the Punch Item belongs to
attachmentsNoJSON request body field — punch Item Assignment attachments. To upload attachments you must upload the entire payload as `multipart/form-data` content-type and specify each parameter as form-data together with `attachments[...
punch_itemYesJSON request body field — the punch item for this Punch List operation
Behavior3/5

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

Annotations indicate readOnlyHint=false and destructiveHint=false, and the description discloses the creation nature and HTTP 201 response. It adds the multipart upload detail for images, but omits other behavioral traits like authentication needs or side effects.

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

Conciseness3/5

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

The description includes verbose API endpoint info and redundant statements ('Create a new Punch List records' twice). It is not extremely concise, but the structure is acceptable with a clear heading for image uploads.

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

Completeness2/5

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

With no output schema, the description should explain the returned object structure and provide more context for a creation tool. It does not mention relationships to sibling tools or what happens after creation (e.g., need to add attachments separately).

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

Parameters4/5

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

Input schema has 100% coverage, and the description adds value by explaining the multipart upload mechanism for images, which is not fully captured in the schema. This helps the agent understand how to format the parameters for file uploads.

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 identifies the action ('Create a new Punch Item') and the resource. However, it does not differentiate from sibling tools like 'add_attachments_to_punch_item' or 'update_punch_item', which would help an agent decide when to use this tool.

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 lists required parameters but provides no guidance on when to use this tool versus alternatives. It lacks explicit when-to-use or when-not-to-use instructions, leaving the agent to infer from context.

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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