Atualiza um(a) Tarefas/providências (o prazo vem no campo deadLine) (OData PATCH /Tasks/{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. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations only state readOnlyHint=false, idempotentHint=false, and destructiveHint=false, so the description carries moderate disclosure burden. It adds useful behavioral context by naming the PATCH method, clarifying that `data` contains fields to alter, and mentioning bulk execution via ids. It does not cover response behavior or error conditions, but with annotations present this is acceptable.
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: two sentences carry the action, endpoint, field semantics, and bulk support. All sentences add value with no repetition of the tool name or obvious 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?
For a simple PATCH-style update tool with no output schema and basic annotations, the description is mostly complete: it identifies the resource, HTTP method, request payload semantics, and bulk capability. It could additionally clarify expected response/return values or error behavior, but these omissions are not critical for basic invocation.
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 0%, so the description must compensate. It does explain the central parameters: `data` are the fields to alter, the endpoint path exposes `id`, and `ids` are for bulk/batched execution. The deadline note ('o prazo vem no campo deadLine') adds further semantic value, though it does not enumerate all possible `data` fields.
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 a specific operation ('Atualiza um(a) Tarefas/providências') with a concrete endpoint ('OData PATCH /Tasks/{id}'). This distinguishes it from sibling create/get/list/update tools by resource and action, and adding the endpoint makes the intent unambiguous.
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 implies use when updating an existing task, and explicitly notes bulk support ('accepts ids for batched execution'). However, it does not state when to prefer this tool over alternatives such as legalone_create_tasks or legalone_get_tasks, and it provides no exclusions or prerequisites.
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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The core legalone_get/list/create/update tools are clearly separated by entity and verb, so common lookups are easy to pick. However, legalone_odata_get and legalone_request duplicate the named CRUD surface, lawsuits vs litigations are near-synonyms in a legal context, and connect/toolkit_info/authenticate have overlapping connection/status duties. Descriptions help resolve most cases, but several tool pairs could still be misselected.
The majority of tools follow a consistent legalone_<verb>_<entity> pattern, which is good. But auxiliary tools break the pattern: legalone_customfield_options, legalone_odata_get, legalone_request, legalone_metadata, authenticate, connect, marketplace, report_bug, show_version, and toolkit_info use bare verbs, nouns, or platform-infrastructure names. The result is mixed conventions that remain readable but are not consistent across the whole set.
With 45 tools, this set is well beyond the 3–15 well-scoped range and above the 25-tool threshold for too many. Many tools are repetitive CRUD variants per entity, plus several infrastructure and marketplace tools that inflate the agent's selection space. A smaller entity-focused set plus one generic OData escape hatch would have covered virtually the same functionality.
Core legal entities like lawsuits, litigations, contacts, appointments, tasks, and updates have create/get/list/update coverage. However, documents, users, areas, service types, and custom field definitions lack named update/delete helpers, and no entity has a dedicated delete tool. The generic legalone_request/odata_get escape hatches fill these gaps, but the lifecycle coverage is uneven.