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by jiezeng2004-design
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TypeScript
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wait_for_task

Poll a task for updates up to 30 seconds, continuing automatically when required, and retrieve the final acceptance evidence.

Instructions

Long-poll a task for up to 30 seconds. If continuation_required=true, call wait_for_task again immediately and do not finish the assistant turn. Terminal responses include get_task_summary acceptance evidence.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "task_id": "<task_id>"
    },
    "name": "wait_for_task"
  }
}

Input Schema

NameRequiredDescriptionDefault
task_idYesTask ID from create_task
wait_secondsNo
timeout_secondsNoPreferred alias for wait_seconds. Maximum 30 seconds to stay within connector request limits.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.5.0

TDQS

B3.4/5.0
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 explains the polling duration, continuation loop, and terminal response contents, but does not explicitly state read-only nature, side effects, or permissions. The timeout behavior on non-completion is also implied but not clarified.

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 two sentences long, front-loads the core action (long-poll a task), and includes necessary additional detail. Every sentence adds value with no repetition or fluff.

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

Completeness2/5

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

Given the complexity of a long-polling tool with 3 parameters and no output schema, the description lacks detail on timeout behavior (e.g., what happens after 30 seconds), the response structure (e.g., how continuation_required is indicated), and any error conditions. The agent lacks key context to fully utilize the tool.

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?

The input schema covers 67% of parameters with descriptions. The tool description adds context for the polling purpose but does not detail parameter semantics beyond what the schema already provides. The baseline of 3 is appropriate as the schema does the heavy lifting.

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

Purpose4/5

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

The description clearly states the tool long-polls a task for up to 30 seconds, specifies continuation behavior, and mentions terminal responses. Although it does not explicitly differentiate from sibling polling tools like get_task_status, the long-poll and continuation loop are distinctive.

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 provides implicit usage guidance by describing continuation logic and terminal responses, but it does not explicitly state when to use this tool over alternatives or when not to use it. The distinction from get_task_status and other task tools is left to the agent to infer.

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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