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midjourney_shorten

Simplify complex Midjourney prompts by analyzing token weights and generating up to 5 shortened versions that retain the dominant ideas.

Instructions

Shorten and analyze a Midjourney prompt using Midjourney's built-in prompt analyzer.

This tool helps optimize long or complex prompts by identifying the most
important elements and producing up to 5 shortened candidate prompts that
preserve the dominant ideas.

Use this when:
- You have a long prompt and want to identify the most impactful words
- You want to understand which parts of your prompt carry the most weight
- You need to simplify a complex prompt while keeping its essence

Returns:
    Up to 5 shortened candidate prompts derived from the original.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesThe prompt to analyze and shorten. Midjourney's prompt analyzer reads the prompt, highlights the highest-weighted tokens and produces up to 5 shortened candidate prompts that preserve the dominant ideas.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description must fully disclose behavior. It describes the process (analyzes tokens, produces candidates) but lacks details on side effects, permissions, rate limits, or whether the tool is read-only. The description is informative but not comprehensive.

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 well-structured with a brief main sentence, a clarifying paragraph, a bulleted use-case list, and a return statement. Every sentence adds value, and the most critical information is front-loaded.

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

Completeness5/5

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

Given the tool's simplicity (one parameter, clear output) and the presence of an output schema, the description covers all essential aspects: what it does, when to use it, and what it returns. No gaps are apparent.

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 parameter is already well-documented. The description adds some context about the analyzer and token weighting, but this does not significantly increase understanding beyond the schema's own description. The baseline 3 is appropriate.

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 verb 'shorten and analyze' and the resource 'Midjourney prompt'. It distinguishes itself from siblings like midjourney_imagine or midjourney_describe by focusing on prompt optimization, and it explicitly lists the output (up to 5 shortened candidates).

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 includes a 'Use this when:' section with three specific scenarios (long prompt, identifying impactful words, simplifying complex prompts). However, it does not mention when not to use the tool or explicitly name alternative siblings, which would strengthen the guidance.

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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