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TylerIlunga

Procore MCP Server

Show Actual Production Quantity

show_actual_production_quantity
Read-onlyIdempotent

Retrieve the full field set for a known actual production quantity, using project_id and id, including crew, location, description, and quantity installed.

Instructions

Return Actual Production Quantity detailed information. Use this when you already know which actual production quantity you want and need its full field set. project_id defaults to the value set by procore_set_config when omitted, and id must identify an existing parent record — resolve it with the matching list tool first. Returns a single JSON object describing the actual production quantity. Read-only — it changes nothing in Procore. Failures come back as an error payload carrying the HTTP status — commonly 401 when the token has expired, 403 without tool permission, and 404 when an id does not resolve. Required parameters: project_id, id, quantity. Procore API: Project Management > Field Productivity. Endpoint: GET /rest/v1.0/projects/{project_id}/actual_production_quantities/{id}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesURL path parameter — unique identifier of the Field Productivity resource
crew_idNoJSON request body field — the ID of the crew for the Actual Production Quantity
quantityYesJSON request body field — amount installed
project_idYesURL path parameter — unique identifier for the project.
descriptionNoJSON request body field — the description of the Actual Production Quantity
location_idNoJSON request body field — the Location ID for the Actual Production Quantity
Behavior5/5

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

Beyond the readOnlyHint annotation, the description adds concrete behavioral details: returns a single JSON object, read-only side effect, error payload with common HTTP status codes (401/403/404), and default project_id behavior from procore_set_config. No contradiction with 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?

Five sentences packed with purpose, usage, defaults, error handling, and endpoint info. Each sentence contributes unique information; no filler or repetition of schema descriptions.

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

Completeness5/5

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

For a simple read tool, the description covers purpose, prerequisites (id resolution), default project_id, return shape, read-only nature, and common failures. The endpoint and API category are also provided, making it self-sufficient despite no output schema.

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?

All 6 parameters are already documented in the schema (100% coverage). The description adds context for project_id (defaults to procore_set_config value) and id (must be resolved via list tool), while confirming the required set. Quantity remains unexplained, but schema covers its meaning.

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 opens with 'Return Actual Production Quantity detailed information,' a specific verb+resource pairing. It further clarifies the use case ('when you already know which actual production quantity you want and need its full field set'), distinguishing this show tool from sibling list/create/update/delete tools.

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

Usage Guidelines5/5

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

Explicitly states when to use this tool: 'Use this when you already know which actual production quantity you want and need its full field set.' It also directs users to 'resolve it with the matching list tool first' for id, implying the list tool is the alternative for discovery. This is clear usage guidance.

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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