Skip to main content
Glama

delegate

Offload multi-step tasks such as research, data compilation, and memory storage to an autonomous sub-agent. It searches the web, reads/writes memory, and delivers concise outcomes.

Instructions

把一件多步骤杂活整体交办给子 Agent。子 Agent 可联网搜索、抓网页、读写记忆库,自主多轮操作后交回最终成果。适合调研汇总、整理资料、把结论存入记忆等。任务描述要自包含。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskYes任务描述,自包含(子 Agent 看不到主对话)
backgroundNo可选:相关背景/已知信息/上下文

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations provided, the description carries the full behavioral disclosure burden. It reveals that the sub-agent can search the web, scrape pages, read/write memory, operate over multiple turns, and return a final result. It also warns that the task must be self-contained because the sub-agent cannot see the main conversation. It stops short of mentioning cost, latency, or side-effect details, but the core behavior is well disclosed.

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 three short sentences with no filler. It front-loads the main action, then gives capability context, examples, and a critical invocation warning. Every sentence earns its place.

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 tool with no annotations and no output schema, the description provides enough for correct selection and invocation: what it does, what the sub-agent can do, typical use cases, and the self-contained task requirement. It could be more complete by explicitly routing simple queries to ask_memory/ask_web and noting possible side effects of memory writes, but overall it is sufficient.

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 coverage is 100%, so the schema already documents task and background. The description adds meaningful semantic guidance: the task parameter should describe a multi-step chore, be self-contained, and target research/organization/memory-writing goals. This goes beyond simply restating the schema.

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?

Description states a specific verb and resource: delegate an entire multi-step chore to a sub-agent. It clearly distinguishes this from the sibling tools ask_memory and ask_web by emphasizing multi-step autonomous execution rather than a single direct query.

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?

The description gives concrete suitable use cases: research summarization, organizing materials, and storing conclusions into memory. It implies this is for whole tasks that need multiple steps, but it does not explicitly state when not to use it or mention the sibling tools by name as alternatives.

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/Ellen-11/secretary-mcp'

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