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SwamiSasha

meta-social-mcp

by SwamiSasha

fb_get_page_insights

Pull Facebook Page insight metrics—page_impressions, page_engaged_users, page_fans—for any date range, with period options like day, week, or 28 days.

Instructions

Get Facebook Page insight metrics (e.g. page_impressions, page_engaged_users, page_fans).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sinceNoISO date, e.g. 2026-09-01
untilNoISO date, e.g. 2026-09-08
periodNoday
metricsNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden, but it only states that the tool gets metrics. It does not disclose how the target page is identified given that the input schema has no page_id parameter, nor what defaults apply when since/until are omitted, nor any limitations on metric availability.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single front-loaded sentence with no filler, and the examples reinforce the most important parameter. It is concise, though slightly too terse to carry the full selection and usage context an agent needs.

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?

For an insights tool with no annotations and no output schema, the description is too thin. It does not explain that the tool operates on an authenticated Page, what date defaults exist, or how this differs from graph_api_request or ig_get_account_insights, leaving the agent with incomplete context for a correct call.

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

Parameters3/5

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

The description adds concrete example metric values that align with the metrics parameter default, which is helpful. However, since and until already have schema descriptions, and period is an explicit enum, the description adds only marginal semantic value beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Get') and names the exact resource ('Facebook Page insight metrics') with representative metric names. This clearly distinguishes it from sibling tools like ig_get_account_insights, fb_list_posts, or graph_api_request.

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 provides no guidance on when to use this tool versus alternatives such as graph_api_request or ig_get_account_insights. There are no explicit contexts, exclusions, or sibling references, so the agent must infer the appropriate choice from the tool name alone.

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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