procesar_consulta

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

With no annotations provided, the description must carry the full burden of behavioral disclosure. It reveals that the tool performs a multi-step pipeline (tokenization, normalization, filtering, creating/reinforcing context bubbles), which implies modification of internal state. The return of 'processed terms and pool events' gives some insight. However, it does not explicitly state whether the operation is destructive, idempotent, or requires special permissions. The description adds context beyond a simple read/write label but lacks complete safety documentation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: two sentences covering purpose, internal steps, and output. Every phrase adds value, and the information is front-loaded with the key action ('Ingesta: procesa una consulta humana completa'). No superfluous words or repetition.

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

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

Given the tool's complexity (a processing pipeline with potential side effects), the description covers the main steps and output. However, it omits prerequisites (e.g., whether a session must exist via 'crear_sesion'), error conditions, and the meaning of domain-specific terms ('burbujas del contexto', 'piscina'). The output schema exists but is not visible, so the return description is helpful but incomplete. Overall, it is adequate for a basic understanding but lacks depth for safe autonomous use.

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

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

The single parameter 'texto' has no description in the schema (0% coverage), so the description must compensate. It refers to 'una consulta humana completa', suggesting the text is a full query. However, it does not specify expected format, length limits, encoding, or examples. The meaning is partially inferred but not explicitly detailed, leaving room for ambiguity about what constitutes a 'complete human query'.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool processes a human query ('procesa una consulta humana completa') and details the steps: tokenization, normalization to canonical concepts, filtering, and creating/reinforcing context bubbles. It also specifies the output: processed terms and pool events. This is a specific verb+resource with sufficient differentiation from sibling tools like 'consultar' (which likely retrieves without processing) and 'contexto_primado' (which may set context directly).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance is provided on when to use this tool versus alternatives. Siblings like 'consultar', 'contexto_primado', and 'declarar_relacion' exist, but the description does not compare them or explain when this tool is appropriate. The agent must infer from the name and context that it is for initial processing of a full human query, but no exclusion criteria or prerequisites are mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.