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TylerIlunga

Procore MCP Server

list_rfq_responses

Retrieve responses to a specific Request for Quote (RFQ) in Procore to review contractor bids and manage construction procurement.

Instructions

List RFQ Responses. [Construction Financials/Commitments] GET /rest/v1.0/rfqs/{rfq_id}/responses

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rfq_idYesRFQ ID
project_idYesUnique identifier for the project.
contract_idYesContract ID
pageNoPage
per_pageNoElements per page
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 of behavioral disclosure. It mentions 'GET /rest/v1.0/rfqs/{rfq_id}/responses', implying a read-only HTTP GET operation, but doesn't explicitly state safety (e.g., non-destructive), authentication needs, rate limits, or pagination behavior. The description adds minimal context beyond the endpoint, leaving key behavioral traits unspecified.

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 concise with two sentences, but it's not optimally structured. The first sentence ('List RFQ Responses.') is clear but could be more informative. The second sentence includes endpoint details ('[Construction Financials/Commitments] GET /rest/v1.0/rfqs/{rfq_id}/responses'), which adds technical context but may clutter the description. It's efficient but lacks front-loaded clarity on usage or constraints.

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 insufficient. It doesn't explain the return format, pagination behavior (implied by 'page' and 'per_page' but not described), or error conditions. For a list operation with multiple required IDs, more context on how responses are filtered or structured 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 input schema (e.g., 'rfq_id', 'project_id', 'contract_id', 'page', 'per_page'). The description adds no additional parameter semantics beyond the endpoint path hint ('rfqs/{rfq_id}/responses'), which aligns with the schema. 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.

Purpose4/5

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

The description clearly states the verb ('List') and resource ('RFQ Responses'), making the purpose specific and understandable. It distinguishes itself from siblings by focusing on RFQ responses rather than other entities like bids or RFQs themselves. However, it doesn't explicitly differentiate from other list tools for RFQ responses (if any exist), which prevents a perfect score.

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. It lacks context about prerequisites (e.g., needing an RFQ ID), exclusions, or comparisons to sibling tools like 'list_rfqs' or 'list_rfq_quotes'. Without such information, the agent must infer usage from the tool name and parameters alone.

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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