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action-queue动作队列

Agent Skill

action-queue 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

269

周安装

11

GitHub Stars

37

下载量

87
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:action-queue(动作队列)
来源仓库:https://github.com/simhacker/moollm
仓库路径:skills/action-queue
安装命令:
npx skills add https://github.com/simhacker/moollm --skill action-queue
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/simhacker/moollm --skill action-queue

简介

action-queue 用于查找、检索和筛选相关信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词或任务场景快速定位候选结果时使用。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装,需结合原始 README 核验具体用法。
  • 安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写操作。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

Action Queue

*"Queue up what to do next. The Sims showed us the way."*

What Is It?

Action Queue is The Sims-inspired task scheduling: instead of doing one thing at a time, you queue up a sequence of actions that execute in order.

While return-stack tracks *where you've been*, action-queue tracks *what you're going to do*.


The Sims Connection

In The Sims, you click multiple actions and they queue up:

Sim's Queue:
  1. Go to fridge     [executing]
  2. Get snack
  3. Eat snack
  4. Watch TV
  5. Go to bed

The Sim works through them in order. You can:

  • Add more actions
  • Cancel any action
  • Reorder the queue
  • Insert urgent actions at the front

Objects push actions too! When you try to eat, the fridge pushes "get food" onto the queue. The food pushes "prepare" and "cook". The stove pushes "serve". Each object dangles the next carrot.

MOOLLM does the same for agents and characters.


The Food Chain Pattern

Objects guide you through multi-step processes by pushing actions:

> DO eat

Fridge intercepts:
  "You need food first."
  → pushes GET-FOOD to front

Queue: [GET-FOOD, EAT]

Food intercepts:
  "This needs preparation."
  → pushes PREPARE to front

Queue: [PREPARE, GET-FOOD, EAT]

Stove intercepts:
  "Needs cooking."
  → pushes COOK to front

Queue: [COOK, PREPARE, GET-FOOD, EAT]

Agent executes in order:
  1. COOK (at stove)
  2. PREPARE (at counter)
  3. GET-FOOD (from fridge)
  4. EAT (finally!)

Dangling a carrot in front of a donkey. Each object advertises what it needs, pushing prerequisites onto the queue. The agent surfs the possibility space of advertisements, guided step by step.

Why This Works

  • No hardcoded recipes — objects know their own prerequisites
  • Emergent behavior — complex sequences from simple rules
  • Interruptible — cancel anytime, queue adapts
  • Discoverable — agent learns by trying
  • Adapts to context — different appliances, different paths
  • Handles routing — crowded kitchen? Find another way

Routing Around Problems

> DO cook

Stove advertises COOK... but:
  "Blocked! Alice is using the stove."
  → Checks alternatives
  → Microwave advertises COOK (score: 70)
  → pushes USE-MICROWAVE instead

Queue: [USE-MICROWAVE, PREPARE, GET-FOOD, EAT]

If the kitchen is crowded:

Kitchen has 4 Sims blocking workspaces.
Counter: "Blocked by Bob"
Stove: "Blocked by Carol"
Fridge: "Accessible!"

Agent routes around obstacles:
  → Wait for counter? (cost: time)
  → Use outdoor grill? (cost: distance)
  → Order takeout? (cost: money)

Highest-scored alternative wins.

Emergent traffic flow. No pathfinding algorithm needed — objects simply advertise availability, agents pick the best option. Crowded rooms naturally disperse as scores drop.

This is how The Sims creates rich behavior from simple object definitions.


Commands

CommandEffect
DO actionAdd action to end of queue
NEXTExecute next queued action
QUEUEShow current queue
URGENT actionInsert at front of queue
CANCEL nRemove action #n from queue
CLEAREmpty the queue
REORDER n mMove action #n to position #m
PAUSEStop executing, keep queue
RESUMEContinue executing queue

Example Session

> DO examine-workbench
Added: examine-workbench

> DO craft-tool
Added: craft-tool

> DO go-north
Added: go-north

> QUEUE
Action Queue:
  1. examine-workbench
  2. craft-tool
  3. go-north

> NEXT
Executing: examine-workbench
You examine the workbench. It has blueprints and tools.

> URGENT check-inventory
Inserted at front: check-inventory

> QUEUE
Action Queue:
  1. check-inventory    ← urgent
  2. craft-tool
  3. go-north

Autonomous Execution

For autonomous agents, the queue runs automatically:

# agent.yml
mode: autonomous
action_queue:
  - examine: hypothesis.yml
  - analyze: data/
  - write: findings.md
  - notify: user

execution:
  auto_advance: true
  pause_on_error: true
  pause_on_user_input: true

Agent works through queue until done, paused, or interrupted.


Queue + Stack Together

Return stack and action queue complement each other:

Return StackAction Queue
Where you've beenWhat you'll do
PastFuture
BACK to revisitNEXT to advance
Navigation historyTask schedule
Saved contextsPending actions

Together they form a complete temporal model:

  • Stack = memory of the past
  • Queue = intentions for the future
  • Current = the present moment

Compound Actions

Queue items can be compound:

> DO [go-to-library, find-book, read-chapter-1]
Added compound action (3 steps)

> QUEUE
Action Queue:
  1. [go-to-library, find-book, read-chapter-1]  (compound)
  2. write-summary

Compound actions expand when executed:

> NEXT
Expanding compound action...
Action Queue:
  1. go-to-library     [executing]
  2. find-book
  3. read-chapter-1
  4. write-summary

Conditional Actions

Actions can have conditions:

action_queue:
  - action: craft-tool
    if: has_materials

  - action: gather-materials
    if: not has_materials

  - action: test-tool
    after: craft-tool

The queue adapts based on state.


Integration with Advertisements

Objects advertise actions. The agent queues the best ones:

Agent enters workshop.

Objects advertise:
  workbench: CRAFT (90), EXAMINE (50)
  bookshelf: READ (70)
  door: EXIT (40)

Agent queues:
  1. CRAFT at workbench (highest score)
  2. READ at bookshelf (if time permits)

Advertisements suggest. Queue commits.


Implementation

# character.yml
name: researcher
location: ./lab

action_queue:
  - action: analyze-sample
    target: sample-A
    added: "2024-01-15T10:00:00"

  - action: write-notes
    target: notebook
    added: "2024-01-15T10:01:00"

  - action: report-findings
    target: user
    added: "2024-01-15T10:02:00"

queue_state:
  paused: false
  current_index: 0
  mode: manual  # or autonomous

Dovetails With


Protocol Symbol

ACTION-QUEUE

Invoke when: Scheduling sequences of actions, autonomous agent behavior.

See: PROTOCOLS.yml

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

35.9%
按下载量换算31

Claude

29.11%
按下载量换算25

Cursor

18.7%
按下载量换算16

Gemini CLI

9.66%
按下载量换算8

安全审计

Gen Agent Trust Hub

未通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

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来源信息

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