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TylerIlunga

Procore MCP Server

Create A Manual Forecast Line Item

create_a_manual_forecast_line_item

Creates a manual forecast line item in Procore to add budget records. Specify project, budget line item or WBS code, and optional details like quantity and cost.

Instructions

Create a manual forecast line item for a budget line item. Use this to create a new Budget records in Procore. Creates a new Budget records and returns the created object on success (HTTP 201). Required parameters: project_id. Procore API: Construction Financials > Budget. Endpoint: POST /rest/v1.0/projects/{project_id}/manual_forecast_line_items

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYesURL path parameter — unique identifier for the project.
budget_line_item_idNoJSON request body field — identifier of the parent budget line item. NOTE - budget line item id or wbs code id is required
wbs_code_idNoJSON request body field — wbs code id of the parent budget line item. NOTE - budget line item id or wbs code id is required
descriptionNoJSON request body field — the description for this Budget operation
quantityNoJSON request body field — the quantity for this Budget operation
uomNoJSON request body field — unit of measure
unit_costNoJSON request body field — the unit cost for this Budget operation
amountNoJSON request body field — total amount
Behavior3/5

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

The description indicates creation behavior and HTTP 201 response. Annotations already mark it as non-readonly and non-destructive. No additional behavioral traits (e.g., idempotency, side effects) are disclosed, but there are no contradictions.

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 is three sentences but contains repetition (e.g., 'Budget records' used twice) and includes unnecessary API details. It could be more concise and focused.

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 8 parameters and no output schema, the description provides basic purpose and endpoint but does not explain constraints like mutual exclusivity between budget_line_item_id and wbs_code_id. It lacks sufficient context for an agent to fully understand parameter dependencies.

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 coverage is 100% with descriptions for all 8 parameters. The description only mentions 'Required parameters: project_id' and does not add meaning beyond the schema, so baseline of 3 is appropriate.

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

Purpose5/5

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

The description clearly states the tool creates a manual forecast line item, specifies the API endpoint, and indicates the success response. It is distinct from sibling tools like delete_a_manual_forecast_line_item and update_a_manual_forecast_line_item, so purpose is unambiguous.

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

Usage Guidelines3/5

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

The description tells when to use the tool (to create a manual forecast line item) but does not provide guidance on when not to use it or alternatives. There are no explicit exclusions or comparisons with other creation tools, leaving the agent to infer usage 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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