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all-agents-mcp

all-agents-mcp

by Dokkabei97
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TypeScript
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delegate_task

Delegate a task to AI agents, automatically analyzing complexity and routing to either single-agent or parallel multi-agent execution.

Instructions

Delegate a task to agent(s). Automatically analyzes complexity and routes to single or parallel execution.

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": "<task>"
    },
    "name": "delegate_task"
  }
}

Input Schema

NameRequiredDescriptionDefault
taskYesThe task to delegate
agentNoPreferred agent (auto-selected if omitted)
contextNoAdditional context
timeoutNoTimeout in ms
allowParallelNoAllow splitting large tasks across multiple agents

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.2

TDQS

A3.8/5.0
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 does reveal the key behavior of automatically analyzing complexity and routing to single or parallel execution, which is useful. However, it omits details such as timeout handling, default agent selection behavior, or failure modes, leaving gaps in transparency.

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 concise sentences, each earning its place. It front-loads the core action ('Delegate a task to agent(s)') and immediately provides the key differentiator (automatic complexity analysis and routing). No redundancy or wasted words.

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 tool has one required parameter, no output schema, and no annotations, the description provides a sufficient high-level understanding of its purpose and key routing behavior. It lacks details about return values or edge cases, but for a tool with auto-routing, the description is fairly complete and actionable.

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 coverage is 100%, so the baseline is 3. The description adds minimal parameter-specific meaning beyond noting parallel execution capability, which is already partially reflected in the allowParallel parameter. The schema itself provides clear descriptions for all parameters, so no extra semantics are needed.

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 uses a specific verb ('Delegate') and resource ('task to agent(s)'), and immediately adds the distinguishing behavior of automatically analyzing complexity and routing to single or parallel execution. This clearly differentiates it from siblings like ask_agent or collaborate by emphasizing the auto-routing functionality.

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 a use case for tasks that may benefit from automatic complexity-based routing, but it does not explicitly state when to prefer this over alternatives like ask_agent or collaborate, nor does it mention any exclusions. The guidance is indirect and not fully developed.

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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