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heyjustinai

Prompt Ops MCP

by heyjustinai

promptenhancer

Transform basic prompts into comprehensive, well-structured versions using a two-step optimization process that first provides guidelines then refines the prompt for enhanced effectiveness.

Instructions

A prompt optimization tool that guides you through transforming basic prompts into comprehensive, well-structured prompts.

How it works:

  1. First call: Provide an originalPrompt to receive optimization guidelines

  2. The LLM follows the guidelines to create an optimized version

  3. Second call: Provide the optimizedPrompt to get it ready for use

This tool uses a meta-prompting approach where the LLM does the actual optimization work.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
originalPromptNoThe original prompt you want to optimize
optimizedPromptNoThe optimized prompt created by following the guidelines
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It explains the two-call workflow and meta-prompting approach, which adds useful behavioral context. However, it doesn't disclose important traits like whether this requires specific permissions, rate limits, error handling, or what the response format looks like. For a tool with no annotations, this leaves significant gaps in behavioral understanding.

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?

The description is well-structured with a clear purpose statement followed by a numbered 'How it works' section and a concluding explanation of the approach. It's appropriately sized and front-loaded with the most important information. The final sentence about meta-prompting could potentially be integrated more seamlessly, but overall it's efficient with minimal waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (two-step process with different parameter usage patterns), no annotations, and no output schema, the description provides a reasonable foundation but has significant gaps. It explains the workflow but doesn't cover what the tool returns, error conditions, or detailed behavioral expectations. For a tool with this level of complexity and no structured support, the description should do more to compensate.

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%, so the schema already documents both parameters thoroughly. The description adds some context by explaining when each parameter should be used (originalPrompt for first call, optimizedPrompt for second call), but doesn't provide additional semantic meaning beyond what the schema already states. This meets the baseline expectation when schema coverage is high.

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 the tool's purpose: 'A prompt optimization tool that guides you through transforming basic prompts into comprehensive, well-structured prompts.' It specifies the verb ('guides you through transforming'), resource ('prompts'), and distinguishes it as a meta-prompting approach. With no sibling tools, this level of specificity is excellent.

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 provides clear usage context through the 'How it works' section, explaining the two-step process: first call with originalPrompt, second call with optimizedPrompt. However, it doesn't explicitly state when NOT to use this tool or mention alternatives, which prevents a perfect score. With no sibling tools, the guidance is adequate but could be more comprehensive.

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

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