insights_pull_insights
Queue a fresh pull of standard Meta insight rows
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| days | No |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| message | No | ||
| retryable | No | ||
| support_ref | No |
Queue a fresh pull of standard Meta insight rows
| Name | Required | Description | Default |
|---|---|---|---|
| days | No |
| Name | Required | Description | Default |
|---|---|---|---|
| message | No | ||
| retryable | No | ||
| support_ref | No |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=false and destructiveHint=false, and the description adds the notion of a 'fresh pull', implying it refreshes or updates insight data. This adds a small amount of context beyond annotations, but it does not disclose any side effects, rate limits, or what exactly happens to existing rows. The description adds modest value but leaves important behavioral details unspecified.
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 sentence with no filler, which is concise. However, it is so terse that it omits essential details like parameter meaning and usage context, making it under-specified rather than appropriately concise. It is front-loaded with the core action, but brevity comes at the cost of completeness.
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?
The tool has a single optional parameter and an output schema, but the description does not explain what 'standard Meta insight rows' means, how the queue behaves, or what the output represents. It does not need to describe return values if an output schema exists, but it still should clarify the parameter and any important behavior. For a tool that initiates a pull, this is insufficient for an agent to call 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?
The schema has a single parameter 'days' with default 30, and schema description coverage is 0%. The description does not mention the parameter at all, so an agent has no indication of what 'days' controls, its valid range, or its effect on the pull. This is a critical gap because the description fails to compensate for the missing schema description.
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 uses a specific verb 'Queue a fresh pull' and identifies the resource as 'standard Meta insight rows', making the core action clear. It does not explicitly differentiate from sibling tools like insights_query_overview or insights_get_date_range, but the action of queueing a refresh is distinct enough for an agent to infer a difference, though not with high confidence.
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?
No guidance is provided on when to use this tool versus the many other insights tools (e.g., insights_export_csv, insights_get_date_range, insights_query_overview). The description does not state any conditions, prerequisites, or exclusions, leaving the agent to guess the appropriate context.
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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