aya_memoria_obter_contexto_retomada

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

No annotations are provided, so the description carries the full burden of behavioral disclosure, and it only reveals that the tool reads memory. It does not state the output format, what happens when no memory/checkpoint exists, whether the operation is idempotent and safe, or whether it depends on prior state. For a tool whose sole job is resuming context, this is a significant gap.

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 a single front-loaded sentence with zero filler — every word carries meaning. It is efficient and clean, though so terse that it sacrifices behavioral context that could have been conveyed in the same space.

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?

Despite low schema complexity, this tool has no output schema and no annotations, so the description is the only source of operational detail. It fails to explain what the returned context looks like, whether it can be called before any checkpoint exists, or how it relates to the checkpoint/initialization siblings in the same family. An agent has enough to guess the intent but not enough to trust the call.

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 input schema is empty (0 parameters), so the rubric baseline is 4. No parameter explanation is needed and the description omits none, since there is nothing to document. It adds no parameter meaning, but none is required.

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 names a specific action ('Le' = Reads) and resource ('memoria minima' = minimal memory), and adds the purpose clause 'para outra LLM continuar' (for another LLM to continue), which goes beyond a pure restatement of the name. However, it does not differentiate from siblings such as aya_framework_montar_contexto or aya_memoria_criar_checkpoint, and 'memoria minima' is left vague.

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?

There is no guidance on when to use this tool versus alternatives. It does not mention that a checkpoint or agent initialization (aya_memoria_criar_checkpoint, aya_memoria_agents_inicializar) may be a prerequisite, nor does it contrast with context-building siblings like aya_framework_montar_contexto_completo. The agent must infer usage entirely from the name.

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