Resumir Andamento

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

No annotations exist, so the description carries the full behavioral burden. It does disclose two valuable traits: it queries DataJud as an external source, and its output contains prompt instructions aimed at the LLM rather than a finished summary. It does not state that the operation is read-only, nor what happens on DataJud lookup failure or when the process number is not found.

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?

Three short sentences, front-loaded with the core behavior and followed by the one non-obvious contract (summarization happens in the model, not the MCP). Slight redundancy between the first two sentences, but no filler.

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?

An output schema exists, so return values need not be explained. The description supplies the one thing an agent could not infer: the response is data plus summarization instructions rather than a ready summary. Only error and availability behavior is left uncovered, which is a minor gap for a two-parameter read tool.

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?

Schema description coverage is 100%, so both parameters (numero_processo in CNJ format, optional tribunal) are already documented in the schema. The description adds no format, default, or fallback details beyond that, so the baseline of 3 applies.

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 uses a specific verb and resource ('Retorna dados estruturados de um processo') and adds a crucial scope clarification: this tool does not produce the summary itself, it returns data formatted with instructions so the model can generate it. That distinguishes it meaningfully from siblings like buscar_processo_por_numero, though it never names that sibling explicitly.

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?

Usage is implied: call this when you need the underlying data to write a summary of a process. The statement that semantic processing 'fica no modelo, não no MCP' implicitly tells the agent it must do the summarization step itself. However, there is no explicit when/when-not guidance nor a named alternative such as buscar_processo_por_numero, which returns process data for other purposes.

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