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j0hanz

PromptTuner MCP

Fix Prompt

fix_prompt
Read-only

Refine and polish prompts to improve clarity, readability, and flow for AI assistants.

Instructions

Polish and refine a prompt for better clarity, readability, and flow.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesPrompt to polish and refine
Behavior3/5

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

Annotations indicate readOnlyHint=true (safe read operation), openWorldHint=true (broad applicability), and idempotentHint=false (non-idempotent). The description adds context by specifying the refinement goals (clarity, readability, flow), which goes beyond the annotations. However, it does not disclose other behavioral traits like potential side effects, rate limits, or detailed output expectations, keeping the score moderate.

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 a single, efficient sentence that front-loads the core action ('polish and refine') and purpose. It avoids redundancy and wastes no words, making it highly concise and well-structured for quick understanding.

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 moderate complexity (single parameter, no output schema), the description is adequate but has gaps. It explains what the tool does but lacks details on when to use it versus siblings, output format, or error handling. With annotations covering safety and scope, it meets minimum viability but isn't fully comprehensive.

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?

The input schema has 100% description coverage, fully documenting the single parameter 'prompt'. The description does not add any parameter-specific semantics beyond what the schema provides (e.g., it doesn't explain format or constraints). With high schema coverage, the baseline score is 3, as the description doesn't compensate but doesn't need to.

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 clearly states the tool's purpose with specific verbs ('polish and refine') and the resource ('a prompt'), and it specifies the improvement goals ('better clarity, readability, and flow'). However, it does not explicitly distinguish this tool from its siblings (boost_prompt, crafting_prompt), which would be needed for a score of 5.

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?

The description provides no guidance on when to use this tool versus its siblings (boost_prompt, crafting_prompt) or any alternatives. It lacks explicit instructions on context, prerequisites, or exclusions, offering only a general purpose without usage differentiation.

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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