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calypsoCodex

HubSpot MCP Extended

by calypsoCodex

post-crm-v3-associations-var-var-batch-read_read

Read batch associations between HubSpot objects by supplying object IDs and properties. Retrieve association data for multiple records in one request.

Instructions

Read a batch of associations. REQUIRES body parameter with object IDs and properties to retrieve. Example: {body: {inputs: [{"id": "123"}, {"id": "456"}], properties: ["firstname", "lastname", "email"], propertiesWithHistory: []}}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputsYesArray of items
toObjectTypeYesPath parameter toObjectType
fromObjectTypeYesPath parameter fromObjectType
Behavior2/5

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

With no annotations, the description must fully disclose behavioral traits, but it only shows a request example. It implies a read operation but does not describe response format, pagination, rate limits, or any side effects. The mention of 'REQUIRES body' is helpful but insufficient for an operation without an output schema or safety annotations.

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 brief, consisting of one sentence plus an example, and is not overly wordy. However, the example is a run-on JSON-like structure that is not well-formatted or clearly separated, which reduces readability. The structure could be improved by using a code block or clearer labels.

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 tool has no output schema and no annotations, the description should provide more operational context, such as expected response fields or error conditions. It only covers the request side, leaving the return value and other important behaviors unexplained. This makes the tool incomplete for an agent to correctly interpret results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema defines fromObjectType, toObjectType, and inputs (each item with id). The description's example adds 'properties' and 'propertiesWithHistory' as top-level body fields, which are not present in the schema, creating a contradiction. While it attempts to illustrate usage, it introduces unsupported parameters that could mislead an agent. The schema coverage is high, but the description's example conflicts with the structured definition.

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 'Read a batch of associations,' providing a specific verb and resource. It matches the tool name and gives a concrete example, making the purpose evident. However, it does not explicitly mention the two object types (fromObjectType/toObjectType) involved, which would further distinguish it from other batch-read tools.

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 gives no guidance on when to use this tool versus alternatives (e.g., single-association reads or batch reads for other object types). The only contextual information is a requirement for a body parameter, which is more about request construction than usage scenarios. There are no exclusions or 'when not to use' notes.

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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