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osAlhaddad1

instagram-mcp

by osAlhaddad1

instagram_unfollow_user

Idempotent

Unfollow an Instagram user using their handle or numeric ID. Requires write access enabled. Returns confirmation and user ID.

Instructions

Unfollow a user as the logged-in account.

Requires INSTAGRAM_ALLOW_WRITES=true.

Args: username: The handle to unfollow. user_id: The numeric id, if you already have it.

Returns: unfollowed (bool) and user_id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
user_idNoNumeric user id. Use instead of username.
usernameNoHandle to unfollow, e.g. 'nasa'.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Annotations already indicate readOnlyHint=false and destructiveHint=false, but the description adds valuable context: the INSTAGRAM_ALLOW_WRITES=true requirement and the return format (unfollowed (bool) and user_id). This goes beyond what annotations provide, helping the agent understand the write-flag dependency and expected output. There is no contradiction with annotations.

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 front-loaded with the core purpose and then structured into requirements, arguments, and returns. Every sentence contributes: the first line states the action, the second gives a critical prerequisite, and the Args/Returns sections are terse and informative. No redundancy, ideal length for a simple mutation tool.

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?

The description covers the essential aspects for a two-parameter mutation: purpose, write-flag requirement, parameter semantics, and return values. It lacks only explicit edge-case handling (e.g., unfollowing a non-existent user) but that's arguably minor given the tool's simplicity and the annotations covering idempotency. Overall, an agent has enough to call it correctly.

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 100%, so the schema already documents both parameters with descriptions. The description adds only a slight nuance—'if you already have it' for user_id—suggesting a preference for username but not materially improving comprehension. Per the rubric, a 3 baseline is appropriate when the schema carries the meaning.

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 states a specific verb (unfollow) and resource (user as the logged-in account), clearly distinguishing it from the sibling follow_user. The first line 'Unfollow a user as the logged-in account' is unambiguous and leaves no doubt about the tool's function.

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?

The description provides a prerequisite (INSTAGRAM_ALLOW_WRITES=true) but gives no explicit guidance on when to use this tool versus alternatives like follow_user or other mutation tools. It does not state conditions like 'use when the client wants to stop following a handle' or indicate when not to use it. The purpose is implied but routing is left to inference.

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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