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Agent Task Confirm

Community
aAAaqwq
agent-task-confirm

Use when confirming whether a dispatched agent task was actually received, activated, and progressing after sessions_send or other task handoff actions.

Overview

PublisheraAAaqwq
RepositoryAGI-Super-Team
Skill nameagent-task-confirm
Stars
98
Forks
23
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by aAAaqwq on GitHub. Read the source before you install it.

Installation

Install the Agent Task Confirm AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/aAAaqwq/AGI-Super-Team.git /tmp/AGI-Super-Team
mkdir -p .claude/skills
cp -r /tmp/AGI-Super-Team/skills/agent-task-confirm .claude/skills/agent-task-confirm
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Agent Task Confirm in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Agent Task Confirm on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Agent Task Confirm is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Agent 任务派发与确认机制

确保每次派发任务后,agent 确实收到并在执行。

触发条件

  • 每次通过 sessions_send 派发任务后自动执行
  • "检查员工状态"、"任务确认"

派发后确认流程

Step 1: 派发任务

sessions_send(sessionKey="agent:<id>:telegram:group:-1003890797239", message="【CEO指令】...")

Step 2: 立即确认送达(30秒内)

sessions_list(activeMinutes=5, kinds=["agent"], messageLimit=0)

检查目标 agent 的 session 是否 active(updatedAt 在最近 60 秒内)。

Step 3: 判断状态

状态判断条件处理
✅ 已接收session active, updatedAt 刚更新等汇报
⚠️ 可能卡住session active 但 5min+ 无新消息发催促消息
❌ 未接收session 不在 active 列表重发一次,仍失败则报告 Daniel

Step 4: 超时催促(5分钟无汇报)

如果 agent 5 分钟内没有发群里汇报,发催促:

sessions_send(sessionKey="agent:<id>:...", message="【催促】你的任务完成了吗?立即用 message 发群里汇报进度。")

Step 5: 死亡判定(10分钟无响应)

如果催促后 5 分钟仍无反应:

  1. 检查 agent 的 session 是否报错(abortedLastRun)
  2. 报告 Daniel:"小X 可能卡住了,需要检查"
  3. 考虑重新派发给其他 agent

每次派发的标准模板

任务消息必须包含:

  1. 【CEO指令】开头
  2. 具体任务描述
  3. 文件写在哪里
  4. 完成后的 message 汇报指令(含 accountId)
  5. "不发群里 = 任务没完成"

批量检查命令

快速检查所有 agent 状态:

sessions_list(activeMinutes=10, kinds=["agent"], messageLimit=1)

看每个 agent 的 updatedAt 和最后一条消息判断是否在工作。

Frequently asked questions

What does the Agent Task Confirm AI skill do?

Use when confirming whether a dispatched agent task was actually received, activated, and progressing after sessions_send or other task handoff actions.

Why use Agent Task Confirm on TypingMind?

Because you install it once and use it with any model. Agent Task Confirm is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Agent Task Confirm in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/aAAaqwq/AGI-Super-Team/tree/main/skills/agent-task-confirm. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Agent Task Confirm?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Agent Task Confirm?

As many as you like. As long as a model supports skills, you can use Agent Task Confirm with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Agent Task Confirm AI skill free?

Yes. It is published on GitHub by aAAaqwq under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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