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agloop-mcp

by zebbern

agloop_get_task

Get task status, dependencies, acceptance criteria, and result log by task ID. Inspect the full details of any task to understand its progress and outcomes.

Instructions

Get details for a single task by ID. Returns task status, dependencies, acceptance criteria, and result log.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
task_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The MCP tool handler for 'agloop_get_task'. Decorated with @mcp.tool(), it accepts a task_id string, delegates to StateManager.get_task(), and returns the task as JSON or an error message.
    @mcp.tool()
    def agloop_get_task(task_id: str) -> str:
        """Get details for a single task by ID. Returns task status, dependencies, acceptance criteria, and result log."""
        task = _sm().get_task(task_id)
        if not task:
            return json.dumps({"error": f"Task '{task_id}' not found"})
        return json.dumps(asdict(task), indent=2)
  • StateManager.get_task() — the core helper that loads the full state from .agloop/state.json (or recovers from a checkpoint), then iterates through tasks to find the one with the matching ID.
    def get_task(self, task_id: str) -> AgLoopTask | None:
        state = self.get_state()
        if not state:
            return None
        for task in state.tasks:
            if task.id == task_id:
                return task
        return None
  • The AgLoopTask dataclass schema that defines the shape of task data returned by agloop_get_task.
    class AgLoopTask:
        id: str
        title: str
        status: TaskStatus = "pending"
        depends_on: list[str] = field(default_factory=list)
        files_to_modify: list[str] = field(default_factory=list)
        acceptance_criteria: list[str] = field(default_factory=list)
        result_log: str | None = None
        started_at: str | None = None
        completed_at: str | None = None
  • Registration via the @mcp.tool() decorator on the FastMCP instance 'mcp' (line 22). This registers 'agloop_get_task' as an MCP tool.
    @mcp.tool()
    def agloop_get_task(task_id: str) -> str:
Behavior3/5

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

No annotations are provided, so the description must convey behavioral traits. It indicates a read operation (get, returns) but doesn't state safety, error handling, or permissions. It partially meets the burden.

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?

A single 12-word sentence efficiently conveys purpose and return content. No wasted words, front-loaded with verb and resource.

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?

Given the low complexity (1 param, simple output), the description covers the main behavior well. It lists return fields, and an output schema exists (not shown but indicated), so completeness is high.

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

Parameters2/5

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

The only parameter 'task_id' is required but has no schema description (0% coverage). The description merely says 'by ID', adding minimal semantics. It does not specify format or constraints.

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 the tool retrieves details for a single task by ID and lists the returned fields (status, dependencies, acceptance criteria, result log). It distinguishes well from sibling tools like agloop_list_tasks.

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

Usage Guidelines3/5

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

The description implies usage for retrieving a single task's details but provides no explicit when-to-use or when-not-to-use guidance, nor mentions alternatives. The context is adequate but not enriched.

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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