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TylerIlunga

Procore MCP Server

create_equipment_maintenance_log

Record equipment maintenance details including service dates and attachments to track upkeep history and schedule future services.

Instructions

Create Equipment Maintenance Log. [Project Management/Field Productivity] POST /rest/v1.0/companies/{company_id}/managed_equipment_maintenance_logs

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
company_idYesUnique identifier for the company.
managed_equipment_idNoEquipment Id the maintenance log is associated with
last_service_dateNoThe Date the equipment was last services
next_service_dateNoNext service date for the equipment
upload_idsNoThe specified array of upload ids is saved as Managed Equipment Maintenance Logs Attachments.
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It states 'Create' implying a write operation but doesn't disclose behavioral traits like required permissions, whether it's idempotent, what happens on duplicate entries, or error handling. The API endpoint hint ('POST') is minimal and doesn't compensate for the lack of safety or operational context.

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 brief and front-loaded with the core action. The additional API endpoint and category tag are concise but could be considered extraneous. It avoids redundancy, though a bit more structure (e.g., separating purpose from metadata) might improve clarity.

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?

Given the complexity of a creation tool with 5 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what a maintenance log entails, the expected response format, or error conditions. For a mutation tool in a crowded sibling set, more context is needed to guide effective use.

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?

Schema description coverage is 100%, so the schema fully documents all 5 parameters. The description adds no parameter-specific information beyond what's in the schema (e.g., no examples, formatting notes, or constraints). Baseline 3 is appropriate since the schema does the heavy lifting, but the description doesn't enhance understanding.

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 the action ('Create') and resource ('Equipment Maintenance Log'), making the purpose explicit. It also includes a category tag '[Project Management/Field Productivity]' and API endpoint, which adds context. However, it doesn't differentiate from sibling tools like 'create_project_equipment_maintenance_log' or 'create_equipment_log_company', 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.

Usage Guidelines2/5

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. With many sibling tools related to equipment and maintenance logs (e.g., 'create_project_equipment_maintenance_log', 'create_equipment_log_company'), the absence of usage context leaves the agent without direction on selection criteria.

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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