Skip to main content
Glama

get_avg_sentence_length

Calculates the average sentence length in words to measure text readability and complexity.

Instructions

Average sentence length in words.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It only states the basic function, omitting details such as whether the output is a float or integer, how punctuation is handled, or what happens with zero sentences. This leaves the agent guessing about edge cases.

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

Conciseness3/5

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

The description is extremely concise (5 words), which is efficient but at the expense of clarity and completeness. It lacks structure or front-loading of key details. While no sentence is wasted, conciseness here detracts from informativeness.

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?

The tool is simple (one parameter, output schema exists), but the description is insufficient. Without annotations, it fails to explain the return value type, handling of empty input, or relationship to sibling tools. An adequate description would at minimum mention the output format.

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

Parameters1/5

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

The input schema has one parameter 'text' with only a title and type (string). Schema description coverage is 0%, and the tool description does not elaborate on the parameter's meaning, format, or constraints. The description adds no value beyond the schema.

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 'Average sentence length in words' clearly states the tool's purpose: computing the mean number of words per sentence. It uses a specific verb (implicitly 'get') and resource (average sentence length), and the distinct name distinguishes it from sibling text analysis tools.

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?

No usage guidelines are provided. The description does not specify when to use this tool over alternatives, nor does it mention any prerequisites, limitations, or exclusions (e.g., for empty texts or non-English sentences).

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/BlackMount-ai/blackmount-nlp-mcp'

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