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OraCool

instagram-mcp

by OraCool

Instagram media insights

ig_media_insights
Read-onlyIdempotent

Retrieve metrics for a single Instagram post, reel, or story; defaults to media-type metrics when none are specified, supporting only connected account media.

Instructions

Metrics for one post, reel or story. Without metrics, a default set for the media type is used (FEED / REELS / STORY). Only media of the connected account is supported.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
metricsNo
media_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), so the bar is lower. The description adds genuinely non-obvious behavior: a default metric set applies when `metrics` is omitted, and defaults vary by media type (FEED/REELS/STORY), plus the connected-account scope restriction.

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?

Three short sentences with the primary concept front-loaded and no filler. The parenthetical '(FEED / REELS / STORY)' slightly muddles media types with metric sets, but overall it is tight and efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only, 2-parameter metrics tool the core behavior is covered: scope, defaults, and media-type variance. Without an output schema the description could reasonably note the return shape, and it omits the vocabulary of valid metric strings, leaving a gap an agent would hit when specifying custom metrics.

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?

Schema description coverage is 0%, so the description must compensate. It explains the `metrics` parameter's optionality and default fallback well, but `media_id` is never described (though its numeric pattern is self-evident) and no valid metric names are enumerated, despite FEED/REELS/STORY being referenced.

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

Purpose4/5

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

The description names a specific resource (one post, reel or story) and the operation (retrieve metrics), which an agent can distinguish from account-level siblings like ig_account_insights. It stops short of explicitly naming the account-level alternative, but the scope ('one post') is clear.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives useful context — 'Only media of the connected account is supported' — and explains the no-metrics fallback, which implies when calling without metrics is appropriate. However it never states when to prefer this over ig_account_insights or ig_get_media, leaving the sibling choice to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.