Skip to main content
Glama

Writing Style Checker

by io.github.theserverlessdev

Remove duplicate adjacent words

fix_duplicates
Read-only

Remove duplicate adjacent words (case-insensitive, including across line breaks) and return the cleaned text plus the list of words that were removed. Read-only with no side effects: the fix is returned in the response, nothing is written anywhere. Use after check_text reports duplicate words; other issue types are report-only and have no auto-fix.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesThe text to clean by removing duplicate adjacent words

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint=true, and the description reinforces this with 'Read-only with no side effects'. It adds context about the return value (cleaned text plus list of removed words) but does not contradict 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 two sentences, front-loads the core action, and every phrase adds value. No redundant or extra words.

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 low complexity (single parameter, no output schema), the description covers the action, safety, return behavior, and usage context. It does not address edge cases like empty input, but the schema expects a string, so it's adequate.

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%, and the description does not add extra meaning beyond the schema's description of the 'text' parameter. The description focuses on output and usage, not parameter semantics.

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 explicitly states the tool removes duplicate adjacent words with specific details (case-insensitive, across line breaks), and distinguishes from the sibling tool check_text by noting it is used after check_text reports duplicates.

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

Usage Guidelines5/5

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

The description clearly instructs when to use this tool: 'Use after check_text reports duplicate words', and when not: 'other issue types are report-only and have no auto-fix'.

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

All Writing Style Checker toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.6/5.0
Disambiguation5/5

Each tool has a unique, clearly defined purpose: check_text analyzes text for various issues, fix_duplicates specifically removes duplicate words, and list_word_lists provides metadata about the detection lists. No overlap or ambiguity.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern using snake_case (check_text, fix_duplicates, list_word_lists), making them predictable and easy to distinguish.

Tool Count5/5

Three tools is an appropriate count for a focused writing style checker: analysis, one targeted fix, and introspection. The number feels neither too sparse nor excessive for the domain.

Completeness4/5

The set covers the core use case of detecting writing issues and provides one automated fix (duplicates) plus lookups of detection rules. Missing are auto-fixes for other issue types and a tool to configure detectors, but the descriptions explicitly note that only duplicates have auto-fix, so the surface is intentionally scoped.

Resources