calls_batch_read
Retrieve multiple HubSpot call records simultaneously to reduce API requests and manage call data efficiently.
Instructions
Read multiple call records in a single request
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| inputs | Yes |
Retrieve multiple HubSpot call records simultaneously to reduce API requests and manage call data efficiently.
Read multiple call records in a single request
| Name | Required | Description | Default |
|---|---|---|---|
| inputs | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states it's a read operation, implying it's non-destructive, but doesn't disclose behavioral traits like rate limits, authentication requirements, error handling for invalid IDs, or whether it returns partial results on failures. The description is too minimal for a batch operation with complex input.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core purpose and avoids unnecessary elaboration, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a batch read tool with 1 parameter (a nested array of objects), 0% schema coverage, no annotations, and no output schema, the description is inadequate. It doesn't explain input format, output expectations, error behavior, or usage context, leaving significant gaps for an AI agent to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It mentions 'multiple call records' but doesn't explain the 'inputs' parameter structure, what 'id' represents, or the purpose of 'properties' and 'associations' arrays. The description adds minimal semantic value beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Read multiple call records') and scope ('in a single request'), which is specific and distinguishes it from single-read tools like calls_get. However, it doesn't explicitly differentiate from other batch operations like calls_batch_create or calls_batch_update, which would require a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 like calls_get (for single reads) or calls_list (for filtered lists). It mentions 'multiple call records' but doesn't specify thresholds or scenarios where batch reading is preferred over individual calls.
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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