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aya_framework_montar_contexto

Creates a minimal context package for a given task, respecting the tech stack, required skills, LLM model level, and character budget. Delivers only pertinent details to improve response accuracy.

Instructions

Monta pacote minimo de contexto para uma tarefa, respeitando stack, skills, nivel da LLM e budget de caracteres.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
consultaYes
limiteCharsNo
nivelModeloNodesconhecido
arquivosAlvoNo
permitirPesadoNo
Behavior2/5

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

With no annotations at all, the description carries the full burden of behavioral disclosure. It does reveal selection heuristics — respecting stack, skills, LLM level, and character budget — but says nothing about whether the tool reads project files, whether it is read-only, what it returns, how it behaves when the budget cannot be met, or any side effects.

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?

A single tight sentence with a front-loaded verb ('Monta') and no filler. Every word earns its place by specifying the object, the addressee, and the four constraints. There is no redundancy or fluff.

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?

This is a 5-parameter tool with no annotations and no output schema, so a one-sentence description is insufficient. An agent cannot determine the return format, the meaning of arquivosAlvo and permitirPesado, the boundary between this tool and montar_contexto_completo, or what happens when limiteChars is too low for the requested context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It does connect 'nivel da LLM' to nivelModelo and 'budget de caracteres' to limiteChars, and implies consulta is the task being packaged. However, arquivosAlvo and permitirPesado are completely unexplained, and no meaning is added beyond the raw enum/default values already in the schema.

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 states a specific verb and resource: 'Monta pacote minimo de contexto para uma tarefa' (builds a minimal context package for a task), with further qualifiers on stack, skills, LLM level, and character budget. The word 'minimo' implicitly contrasts with the sibling aya_framework_montar_contexto_completo, but the differentiation is implicit rather than explicit, so it loses the top score.

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?

No guidance is given on when to use this tool versus closely related siblings such as aya_framework_montar_contexto_completo, aya_framework_buscar_conteudo, or aya_framework_pack_montar. The 'minimo' qualifier hints at a lightweight-context use case, but there is no explicit when-to-use, when-not-to-use, or alternative-routing information.

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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