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TylerIlunga

Procore MCP Server

create_productivity_log

Create a productivity log to track daily project activities and progress within Procore's project management system.

Instructions

Create Productivity Log. [Project Management/Daily Log] POST /rest/v1.0/projects/{project_id}/productivity_logs

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYesUnique identifier for the project.
productivity_logYesproductivity_log
Behavior2/5

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

No annotations are provided, so the description carries full burden. It states 'Create' implying a write/mutation operation, but doesn't disclose behavioral traits like required permissions, whether it's idempotent, what happens on duplicate creation, or error conditions. The HTTP method 'POST' is mentioned, but no additional context on side effects or limitations.

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. However, it includes technical details like 'POST /rest/v1.0/projects/{project_id}/productivity_logs' which may be redundant if the agent already has API context. The single sentence is efficient but could be more informative.

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?

For a creation tool with no annotations and no output schema, the description is inadequate. It doesn't explain what a productivity log is, what data it expects, what the response looks like, or any error handling. Given the complexity (nested object parameter) and lack of structured guidance, more context is needed for 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 documents both parameters. The description adds no parameter semantics beyond what the schema provides—it doesn't explain what fields 'productivity_log' object should contain or provide examples. Baseline 3 is appropriate when schema does the heavy lifting.

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

Purpose3/5

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

The description states the action ('Create') and resource ('Productivity Log'), but it's vague about what a productivity log actually is or contains. It doesn't differentiate from sibling tools like 'create_work_log' or 'create_daily_construction_report_log', leaving ambiguity about when to use this specific 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?

No guidance is provided on when to use this tool versus alternatives. The description includes a category tag '[Project Management/Daily Log]' which hints at context, but doesn't explicitly state prerequisites, constraints, or compare with similar sibling tools like 'create_daily_construction_report_log' or 'create_work_log'.

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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