datacrazy_conversations_messages_list
Buscar conversa por ID (GET /api/v1/conversations/{id}/messages).
Bulk support: accepts ids for batched execution.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ||
| ids | No | ||
| query | No | ||
| account | No |
Buscar conversa por ID (GET /api/v1/conversations/{id}/messages).
Bulk support: accepts ids for batched execution.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ||
| ids | No | ||
| query | No | ||
| account | No |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds useful behavioral context by naming the exact GET endpoint and disclosing bulk/batched execution support, but it omits details like pagination, filtering behavior, or authentication needs. No contradiction exists.
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 two compact, front-loaded sentences: first the core endpoint, then the bulk behavior. It contains no fluff or repetition. Minor wording could be improved, but the structure is highly efficient.
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?
Basic invocation is understandable: provide id, optionally use ids for batch. However, with no output schema and 0% parameter description coverage, the unexplained query and account parameters leave meaningful gaps. It is adequate for simple calls but not fully complete for all input options.
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 carries the burden of explaining parameters. It clarifies id as the conversation identifier and ids for batched execution, but provides no meaning for query or account parameters. This is only partial compensation for the lack of schema descriptions.
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 identifies the exact endpoint and resource: GET /api/v1/conversations/{id}/messages, so it clearly refers to listing messages for a conversation. This distinguishes it from sibling tools like datacrazy_conversations_list. However, 'Buscar conversa por ID' is slightly ambiguous because it could be read as fetching a conversation rather than its messages.
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 intended use is implied: pass a conversation ID to retrieve its messages, and use ids for batch execution. But there is no explicit guidance about when to prefer this over datacrazy_conversations_list or datacrazy_conversations_messages_create, nor any exclusions or prerequisites.
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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