Skip to main content
Glama
ramvishvas

prompt-enhancement-mcp-server

by ramvishvas

enhance_prompt

Transforms rough prompts into detailed, clear, and effective versions using AI. Supports multiple providers and custom templates.

Instructions

Enhances a user prompt using AI to make it more detailed, clear, and effective

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesThe prompt text to enhance
modelNoModel to use, overriding provider default (optional)
contextNoOptional conversation history for context
providerNoAI provider to use (optional, uses default if not specified)
templateNoCustom enhancement template. Use ${userInput} as placeholder. (optional)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries the full burden but discloses almost nothing: it doesn't mention latency (AI call), cost, whether the original prompt is preserved, what the output looks like, or any rate limits. 'Using AI' implies an external call but no behavioral details follow.

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?

A single efficient sentence that front-loads the core action and outcome. No wasted words or structural issues.

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?

For a 5-parameter AI tool with no annotations and no output schema, the description is insufficient. It omits important behavioral context such as output format, whether context/template alter behavior, and any constraints on the AI enhancement process.

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 coverage is 100%, so the schema already documents all five parameters with descriptions and enums. The description adds no parameter-specific meaning beyond what the schema provides, which meets the baseline of 3 when coverage is high.

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 states a specific verb ('Enhances') and resource ('a user prompt') with clarifying goals ('more detailed, clear, and effective'). It is clear what the tool does, though no sibling tools exist to differentiate from.

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 guidance is provided on when to use this tool versus alternatives, what prerequisites exist, or when not to use it. The description simply states the capability without any context for decision-making.

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

Deploy Server

Other Tools