Skip to main content
Glama
CSOAI-ORG

Writing Assistant Ai MCP

analyze_tone

Analyze text to determine its tone (formal, casual, academic, persuasive, technical, emotional) and style, including active vs passive voice and power word usage.

Instructions

Analyze the tone and style of text. Detects formal, casual, academic, persuasive, technical, and emotional tones. Also checks active vs passive voice and power word usage.

Args: text: The text to analyze

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
api_keyNo
Behavior3/5

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

With no annotations, description must disclose all behaviors. Mentions what it detects, but does not clarify if it is read-only, requires auth (api_key parameter hint), or any side effects. Adequate but not thorough.

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?

Concise and front-loaded with purpose. The Args line is a minor structural hiccup, but overall efficient and clear.

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?

No output schema and no description of return format or interpretation of results. For a text analysis tool, more context on output (e.g., JSON structure, score ranges) is needed.

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

Parameters2/5

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

Schema coverage is 0%; description adds meaning for 'text' (the text to analyze) but completely ignores the 'api_key' parameter. This leaves a significant gap for a required-like optional parameter.

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?

Clearly states the tool analyzes tone and style of text, listing specific tones (formal, casual, academic, etc.) and voice/power word detection. This distinguishes it from siblings like score_readability or generate_headlines.

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?

Implied usage for tone analysis, but no explicit guidance on when to use this tool vs alternatives (e.g., when to use check_similarity instead). No when-not-to-use statements.

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/CSOAI-ORG/writing-assistant-ai-mcp'

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