Get Post Analytics
get_post_analyticsReturn raw analytics for a single published platform target, using the platform-specific metric set.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| platform | Yes | ||
| targetId | Yes |
get_post_analyticsReturn raw analytics for a single published platform target, using the platform-specific metric set.
| Name | Required | Description | Default |
|---|---|---|---|
| platform | Yes | ||
| targetId | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish this as read-only (readOnlyHint=true, destructiveHint=false), and the description adds that it returns 'raw' data and uses a 'platform-specific metric set,' telling the agent the output is unaggregated and varies by platform. It does n't disclose response format, error behavior, or permission requirements, but the safety profile is covered by annotations.
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?
A single sentence with each phrase carrying meaning: the action, the resource scope, the published constraint, and the platform-specificity. There is no filler or redundant re-statement of the tool name.
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 is a simple read-only getter with two parameters and an enum, and the description covers the core invocation context (single, published, platform-specific). However, with no output schema, it leaves the return structure unstated, and 'raw analytics' is vague about actual metric fields and shape.
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 for parameter meaning. It only implies targetId is a single published platform target and that platform affects the metric set, but does n't explain targetId format, required platform values beyond the enum, or how the two parameters combine. This is minimal compensation for an otherwise unannotated 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 identifies a specific action ('Return') and resource ('raw analytics for a single published platform target'). It is distinct enough from get_account_analytics and get_posts_with_analytics because it specifies a single target, though it does n't name these alternatives.
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 phrase 'single published platform target' gives implicit usage context: this is for one already-published post, not drafts or bulk analytics. There is no explicit when-not-to-use guidance or pointer to sibling tools, so guidance is inferred rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.