Skip to main content
Glama

kiro_task_status

Check status and retrieve partial results from async tasks for polling streaming responses in Kiro CLI workflows.

Instructions

Get status and partial results of an async task. Use for polling streaming results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
task_idYesThe task ID returned by kiro_chat_async
from_chunk_indexNoGet chunks starting from this index (for incremental updates)

Implementation Reference

  • The main handler function for the kiro_task_status tool, which extracts arguments and calls the task manager to get status.
    async def _handle_task_status(
        task_manager: StreamingTaskManager,
        arguments: dict[str, Any]
    ) -> dict[str, Any]:
        """Handle kiro_task_status tool call - get task status and partial results."""
        task_id = arguments.get("task_id", "")
        from_chunk_index = arguments.get("from_chunk_index", 0)
        
        status = await task_manager.get_task_status(task_id, from_chunk_index)
        
        if status is None:
            return {
                "error": "Task not found",
                "task_id": task_id,
            }
        
        return status
  • The input schema definition for the kiro_task_status tool, defining required task_id and optional from_chunk_index.
    {
        "name": "kiro_task_status",
        "description": "Get status and partial results of an async task. Use for polling streaming results.",
        "inputSchema": {
            "type": "object",
            "properties": {
                "task_id": {
                    "type": "string",
                    "description": "The task ID returned by kiro_chat_async"
                },
                "from_chunk_index": {
                    "type": "integer",
                    "description": "Get chunks starting from this index (for incremental updates)",
                    "default": 0
                }
            },
            "required": ["task_id"]
        }
    },
  • Dispatch/registration point in the call_tool handler that routes kiro_task_status calls to the specific handler.
    elif name == "kiro_task_status":
        result = await _handle_task_status(task_manager, arguments)
  • Supporting method in StreamingTaskManager that implements the status retrieval logic used by the tool handler.
    async def get_task_status(
        self,
        task_id: str,
        from_chunk_index: int = 0,
    ) -> dict[str, Any] | None:
        """Get task status with new chunks since last poll.
        
        Args:
            task_id: Task ID to check
            from_chunk_index: Get chunks starting from this index
            
        Returns:
            Status dict or None if task not found
        """
        task = self._tasks.get(task_id)
        if task is None:
            return None
        return task.to_status_dict(from_chunk_index)
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'polling streaming results' and 'incremental updates' (via parameter context), which adds useful context about its iterative nature. However, it doesn't specify rate limits, error handling, or what 'partial results' entail, leaving gaps for a polling tool.

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?

The description is extremely concise (two short sentences) and front-loaded with the core purpose. Every word earns its place, with no redundant or vague phrasing, making it easy for an agent to parse quickly.

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

Completeness3/5

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

Given the tool's moderate complexity (polling with incremental updates), no annotations, and no output schema, the description is minimally adequate. It covers the purpose and usage but lacks details on return values, error conditions, or completion states, which are important for a polling operation.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema fully documents both parameters. The description adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't explain task ID format or chunk indexing details). This meets the baseline of 3 when the schema handles parameter documentation.

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's purpose with specific verbs ('Get status and partial results') and identifies the resource ('async task'). It distinguishes itself from siblings like kiro_chat_async (which creates tasks) and kiro_task_list (which lists tasks) by focusing on polling for ongoing task results.

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

Usage Guidelines5/5

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

The description explicitly states when to use this tool ('Use for polling streaming results') and references a specific alternative ('task ID returned by kiro_chat_async'), providing clear context for its application versus other task-related tools like kiro_task_cancel or kiro_task_list.

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/vanphappi/kiro-cli-mcp'

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