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generate_foxbrizio_script

Generate a Foxbrizio Romano-style script from Fabrizio Romano tweets for producing sports transfer news videos.

Instructions

Genera un script épico de Foxbrizio Romano basado en tweets de Fabrizio Romano

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
styleNoEstilo del scriptepic
topicNoTema principal del script (ej: "Haaland", "Real Madrid")fútbol
tweetsYesLista de tweets de Fabrizio Romano para basar el script
word_countNoNúmero objetivo de palabras (recomendado: 75-80)
Behavior2/5

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

With no annotations provided, the description is the only source for behavioral details. It states that a script is generated but does not disclose return format, input requirements (e.g., minimum number of tweets), or potential side effects. The agent is left without a clear picture of what to expect from the tool.

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, focused sentence that immediately conveys the core action and input source. Every word contributes to understanding, with no redundancy or unnecessary padding.

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?

The tool lacks an output schema and annotations, and the description is minimal. It does not explain the return format or how this step fits into the overall Foxbrizio video generation pipeline. The limited context makes it hard for an agent to confidently invoke the tool in the right sequence.

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 schema already provides detailed descriptions for all four parameters (style, topic, tweets, word_count), giving 100% coverage. The description adds no extra semantic value beyond what the schema already contains, so the baseline of 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 'genera' (generate) and the specific deliverable 'script épico de Foxbrizio Romano', anchored on 'tweets de Fabrizio Romano'. This distinguishes it from sibling tools like generate_foxbrizio_audio or generate_foxbrizio_caption, making the tool's purpose unambiguous.

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 gives no explicit indication of when to use this tool versus alternatives such as generate_foxbrizio_caption or generate_complete_foxbrizio_video. There are no mentions of the generation pipeline, prerequisites, or exclusions, so the agent must infer usage solely from the tool name.

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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