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improve_prompt

Analyzes a prompt to provide category scores, improvement suggestions, and an enhanced version for optimal performance.

Instructions

Mejorar prompt con IA — Analiza el prompt actual con IA y devuelve puntuaciones por categoria, sugerencias de mejora y una version mejorada del prompt. Util cuando el usuario quiere saber si su prompt es bueno o como mejorarlo. [query]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesEl prompt a analizar. Si no lo proporciona el usuario, usar el prompt actual (obtener con get_prompt primero)
Behavior2/5

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

No annotations are provided. The main description omits the fallback behavior where the tool uses the current prompt if none is provided, which is only mentioned in the parameter description. Side effects (e.g., does this modify anything?) are not addressed.

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-loading the core action and usage context. Every word serves a purpose with no redundancy or filler.

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?

The description outlines the return items (scores, suggestions, improved version) but lacks detail on format or categories. With no output schema, this is a moderate gap. The fallback behavior is handled in the parameter, but not in the main description.

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% and the parameter 'prompt' includes a detailed description explaining its meaning and fallback logic. The main description adds no further parameter context, meeting the baseline but not exceeding it.

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 identifies the tool's purpose: analyzing a prompt with AI to return scores, improvement suggestions, and an improved version. It distinguishes itself from sibling tools like get_prompt (retrieve only) and save_prompt (persist changes).

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 clear use case: 'Útil cuando el usuario quiere saber si su prompt es bueno o como mejorarlo.' It provides when to use but does not explicitly exclude alternative tools or mention prerequisites, which would elevate clarity.

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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