Skip to main content
Glama

Concluir, adiar ou repriorizar uma tarefa

systemtask_task_update

Update task details: mark as complete or reopen, change due date, priority, estimate, or title. Specify only the fields to modify.

Instructions

Muda o que já existe: marcar concluída, mudar a data, a prioridade, a estimativa ou o título. Só manda o que muda. Para APAGAR uma tarefa, não dá por aqui — é pelo app (o token de agente não apaga nada, de propósito).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dueNoNova data, YYYY-MM-DD.
taskYesO id da tarefa (o número que aparece como #123).
titleNo
priorityNo
completedNotrue marca como feita; false reabre.
descriptionNo
estimateMinNo
Behavior4/5

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

Adds valuable behavioral context beyond annotations: the agent token intentionally cannot delete tasks, and deletions must be done via the app. This explains the destructiveHint=false annotation and clarifies the safety model. The partial-update behavior is also disclosed. No contradiction with annotations.

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

Conciseness5/5

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

Two concise sentences front-load the main purpose and usage pattern, followed by a necessary exclusion. Every sentence earns its place with no fluff or repetition.

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

Completeness4/5

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

For a 7-parameter update tool with no output schema, the description covers the core semantics, partial update behavior, and the deletion caveat. It does not list all editable fields (e.g., description) but schema covers those, and the main fields are addressed. Sufficiently complete for an AI agent to use it correctly.

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

Parameters4/5

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

Schema description coverage is only 43%, so the description compensates by mapping key fields: 'data' to due, 'prioridade' to priority, 'estimativa' to estimateMin, 'título' to title, 'marcar concluída' to completed. The instruction to only send changed fields clarifies that all parameters except task are optional.

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

Purpose5/5

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

The description clearly states it modifies existing tasks, listing specific operations: mark complete, change date, priority, estimate, or title. It distinguishes itself from destructive operations by explicitly stating deletion is not possible through this tool, aligning with the update-focused purpose.

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

Usage Guidelines4/5

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

Provides clear guidance: 'Só manda o que muda' (only send what changes) establishes patch semantics. It also explicitly excludes deletion, directing users to the app instead. However, it doesn't name sibling tools like task_create or task_move as alternatives, leaving some room for ambiguity in tool selection.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/luis1amaral/system-task-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server