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TylerIlunga

Procore MCP Server

show_correspondence_project

Retrieve specific correspondence records for bid packages in Procore projects to track communication and manage preconstruction documentation.

Instructions

Show Correspondence. [Preconstruction/Bid Management] GET /rest/v1.0/projects/{project_id}/bid_packages/{bid_package_id}/correspondences/{id}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYesUnique identifier for the project.
bid_package_idYesBid Package ID
idYesCorrespondence ID
pageNoPage number for pagination
per_pageNoItems per page (max 100)
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 mentions 'GET' implying a read-only operation, but doesn't disclose behavioral traits such as authentication requirements, rate limits, error handling, or pagination behavior (though pagination parameters exist in the schema). The description is minimal and lacks critical 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 concise with two parts: a brief purpose statement and the REST endpoint. It's front-loaded with the action ('Show Correspondence') and wastes no words. However, it could be more structured by separating usage notes from technical details, but it's efficient given its length.

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 (5 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what 'Correspondence' returns, how pagination works with the 'page' and 'per_page' parameters, or any error conditions. For a tool with multiple parameters and no structured output, more context is needed to guide the agent effectively.

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%, with all parameters documented in the schema (e.g., project_id, bid_package_id, id, page, per_page). The description adds no additional parameter semantics beyond the endpoint path, which implies the hierarchical relationship of IDs. Since the schema does the heavy lifting, the baseline score of 3 is appropriate.

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 'Show Correspondence' which indicates a retrieval/display action, but it's vague about what 'Correspondence' entails (e.g., messages, documents). It includes a context tag '[Preconstruction/Bid Management]' and a REST endpoint, which adds some specificity but doesn't fully clarify the resource or distinguish it from sibling tools like 'list_correspondences_project' or 'show_correspondence_company'. The purpose is understandable but lacks detail.

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 explicit guidance on when to use this tool versus alternatives is provided. The description does not mention sibling tools (e.g., 'list_correspondences_project' for listing multiple correspondences) or specify prerequisites like required permissions. Usage is implied through the endpoint structure but not articulated for the AI agent.

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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