Skip to main content
Glama
farukkolip

TikTapDown MCP

calculate_tiktok_engagement_rate

Calculate your TikTok engagement rate from views, likes, comments, shares, and saves. Get benchmarked tier classification and tips to improve engagement.

Instructions

Calculate a TikTok video or account engagement rate and benchmark it against tier averages. Inputs are raw counts; output includes ER percentage, tier classification, and improvement tips.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
likesYesTotal likes
savesNoOptional: saves (TikTok counts these as bookmarks)
viewsYesTotal views
sharesYesTotal shares
commentsYesTotal comments
Behavior4/5

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

With no annotations, the description must disclose side effects. It describes inputs and outputs but does not explicitly state that the tool is read-only or has no side effects. However, the nature of calculation implies no data modification, which is conveyed indirectly. Could be more explicit.

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?

Two sentences effectively communicate purpose and scope, with no redundant information. Well front-loaded.

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 lack of output schema, the description provides a reasonable overview of outputs. However, it could include more detail on how tier averages are determined or the improvement tips, but it is sufficient for most use cases.

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 input schema covers 100% of parameters with descriptions. The description adds value by stating the output components (ER percentage, tier, tips) and that inputs are raw counts, which enhances understanding 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 clearly states it 'Calculates a TikTok video or account engagement rate and benchmark it against tier averages.' The verb 'calculate' specifies the action, and 'engagement rate' distinguishes from sibling tools like RPM calculation or extraction tools.

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

Usage Guidelines4/5

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

The description does not explicitly state when to use this tool over alternatives, but the purpose is distinct from siblings which handle different TikTok metrics. The context of 'raw counts' implies use when raw data is available, but no explicit exclusions.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/farukkolip/tiktapdown-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server