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Readify-App

Instagram MCP Server

by Readify-App

instagram_follower_count

Retrieve Instagram user follower counts by providing a username. Get accurate follower data for analysis, tracking, or verification purposes.

Instructions

Instagramユーザーのフォロワー数を取得します。

Args:
    username: Instagramユーザー名(@なし)

Returns:
    フォロワー数の文字列

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
usernameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
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 burden of behavioral disclosure. It states the tool retrieves follower count but doesn't cover aspects like rate limits, authentication needs, error handling, or whether it's a read-only operation (though implied by '取得します' - get). For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior and constraints.

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

Conciseness5/5

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

The description is well-structured and concise, with zero waste. It uses a clear purpose statement followed by labeled sections for Args and Returns, making it easy to parse. Every sentence earns its place by providing essential information without redundancy.

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

Completeness4/5

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

Given the tool's low complexity (one parameter, no nested objects) and the presence of an output schema (which covers return values), the description is reasonably complete. It explains the purpose, parameter semantics, and return type. However, without annotations, it could benefit from more behavioral context (e.g., rate limits or auth requirements) to fully inform usage.

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

Parameters4/5

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

The description adds meaningful context for the single parameter 'username': it specifies 'Instagramユーザー名(@なし)' (Instagram username without @). This clarifies the expected format beyond what the input schema provides (which has 0% description coverage and only lists 'username' as a string). With one parameter and low schema coverage, the description effectively compensates by adding semantic detail.

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 clearly states the tool's purpose: 'Instagramユーザーのフォロワー数を取得します' (Get Instagram user follower count). It specifies the verb ('取得します' - get) and resource ('Instagramユーザーのフォロワー数' - Instagram user follower count), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'instagram_user_stats' or 'instagram_user_info', which might provide similar or overlapping data.

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. It doesn't mention sibling tools like 'instagram_user_stats' (which might include follower count) or 'instagram_user_info' (which could provide broader user data), nor does it specify prerequisites or exclusions. Usage is implied by the purpose but lacks explicit context for selection.

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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