Atualiza um(a) Processos judiciais com os campos próprios do módulo (valor da causa, partes, pedidos) (OData PATCH /Lawsuits/{id}). data = campos a alterar.
Bulk support: accepts ids for batched execution.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ||
| ids | No | ||
| data | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already state readOnlyHint=false, so 'Atualiza' is not surprising. The description adds valuable behavioral context beyond annotations: it is an OData PATCH operation, `data` represents only the fields to change, and bulk execution via 'ids' is supported. This meaningfully informs the agent without contradicting the annotations.
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 compact and efficient: two sentences deliver the operation, target resource, method, parameter semantics, and batch behavior. There is no filler, and the most important action is front-loaded.
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?
For a straightforward CRUD update tool with 3 params, the description is mostly complete: it explains the update semantics, the PATCH method, and the optional bulk path. It stops short of describing the return value or the exact relationship between the required 'id' and optional 'ids', but it gives enough for a competent agent to use the basic single-update flow reliably.
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 very sparse: `data` is an arbitrary object with no property semantics, and 'ids' is merely an array. The description compensates by explaining that `data` is 'campos a alterar' and that 'ids' enables batch execution, while `id` is shown in the endpoint path. This is useful but could be clearer about id vs ids coordination for batch calls.
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 identifies a specific verb and resource: 'Atualiza ... Processos judiciais' and further specifies the module fields (valor da causa, partes, pedidos) and the HTTP endpoint OData PATCH /Lawsuits/{id}. This distinguishes it from the sibling update/create tools for other LegalOne entities.
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?
The description provides clear context for when to use the tool: it updates existing lawsuit records, optionally in bulk using 'ids'. It does not explicitly compare with create or list alternatives, so it misses the full 5-level, but the usage context is unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.