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return-stack返回堆栈

Agent Skill

return-stack 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

272

周安装

11

GitHub Stars

37

下载量

85
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:return-stack(返回堆栈)
来源仓库:https://github.com/simhacker/moollm
仓库路径:skills/return-stack
安装命令:
npx skills add https://github.com/simhacker/moollm --skill return-stack
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 return-stack

简介

return-stack 用于查找、检索和筛选相关信息,支持基于关键词或线索快速定位候选结果。

  • 适用于 Codex、Claude、Cursor、Gemini CLI 中需要信息聚合与过滤的研究或决策场景。
  • 通过 GitHub 安装,使用 npx skills add 命令添加对应仓库的技能模块。
  • 使用前应确认权限范围和维护状态,警惕是否涉及联网搜索或敏感数据访问。
  • 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

Return Stack

*"Where you've been is where you can go back to."*

What Is It?

Return Stack treats navigation history as a first-class continuation — a stack of saved positions you can manipulate like browser history or a call stack.


The Metaphor

ProgrammingBrowserMOOLLM
Call stackHistoryReturn stack
Return addressBack buttonPrevious room
Stack frameTabRoom context
PushNavigateENTER
PopBackBACK

Commands

CommandEffect
ENTER roomPush current room, enter new one
BACKPop stack, return to previous room
FORWARDRedo after BACK (if available)
HISTORYShow the stack
BOOKMARKSave current position
GOTO bookmarkJump to saved position
STACKShow all open "tabs" (parallel stacks)
FORKCreate new tab from current position

Example Session

> ENTER workshop
[Stack: lobby]

> ENTER storage
[Stack: lobby → workshop]

> ENTER archive
[Stack: lobby → workshop → storage]

> BACK
Returning to storage...
[Stack: lobby → workshop]

> BACK
Returning to workshop...
[Stack: lobby]

> HISTORY
  1. lobby (start)
  2. workshop
  3. storage
  4. archive ← furthest

Current: workshop (position 2)

Bookmarks

Save positions for later:

> BOOKMARK "interesting-spot"
Bookmarked: workshop as "interesting-spot"

> ENTER research
> ENTER data-room
> ENTER sub-analysis
[Deep in the hierarchy]

> GOTO interesting-spot
Returning to workshop...
[Stack cleared, at bookmark]

Forking (Tabs)

Create parallel exploration paths:

> FORK
Created new tab from workshop.
Tab 1: lobby → workshop
Tab 2: workshop (active) ←

> ENTER experiment-A
[Tab 2: workshop → experiment-A]

> STACK
Tab 1: lobby → workshop
Tab 2: workshop → experiment-A ←

> TAB 1
Switching to Tab 1...
[Now at workshop via tab 1]

As Continuation

The return stack IS a continuation:

# Stored in character's pocket
return_stack:
  - path: "./lobby"
    context: {examining: "welcome-sign"}
  - path: "./workshop"
    context: {crafting: "blueprint-v2"}
  - path: "./storage"
    context: {searching: "rare-materials"}

# Current position
current: "./archive"
context: {reading: "old-records"}

When you BACK, you don't just return to the room — you restore the context you had there.


Portable Journey

The stack travels with you:

> INVENT
Inventory:
  - notebook
  - pen
  - return_stack: [lobby → workshop → storage]

You can:

  • Save your journey to a file
  • Share it with others
  • Replay someone else's exploration
  • Branch from any point in their journey

HyperCard Heritage

HyperCard had:

  • Stacks of cards
  • "Go back" button
  • Breadcrumb trail
  • Bookmarks

MOOLLM extends this:

  • Rooms as cards
  • BACK command
  • Return stack as data
  • Bookmarks as saved positions
  • FORK for parallel exploration

Implementation

# character.yml
name: explorer
location: ./archive

navigation:
  return_stack:
    - room: ./lobby
      entered: "2024-01-15T10:00:00"
    - room: ./workshop
      entered: "2024-01-15T10:05:00"
      context:
        active_task: "crafting"
    - room: ./storage
      entered: "2024-01-15T10:15:00"

  bookmarks:
    interesting-spot:
      room: ./workshop
      context: {task: "blueprint-review"}
    start:
      room: ./lobby

  forward_stack: []  # After BACK, stores where you came from

Dynamic Deoptimization

The Self programming language (source of our prototype inheritance) pioneered dynamic deoptimization: aggressively inlining code for performance, then reconstructing the "logical" call stack on demand when debugging.

The LLM does this naturally for narrative:

SelfMOOLLM
Inlined bytecodeFlattened conversation
Deoptimized framesReconstructed causality
Breakpoint trigger"How did we get here?"
Stack traceCausal chain from evidence

The stack isn't explicitly maintained, but it's recoverable.

How It Works

When you ask for history, the LLM examines:

evidence_sources:
  - session_log: "Append-only narrative trail"
  - room_state: "Accumulated changes"
  - character_location: "Current position"
  - file_timestamps: "Order of modifications"
  - chat_context: "Recent decisions"

And synthesizes a virtual stack trace:

Deduced navigation:
1. lobby (start)
2. workshop (examining blueprints)
3. storage (found locked chest)
4. workshop (returned for key) ← BACK
5. storage (unlocked chest)
6. archive (following map) ← current

This is introspection without instrumentation — the same insight that made Self's debugger magical.


Dovetails With


Protocol Symbols

RETURN-STACK      — Navigation history as data
BACK / FORWARD    — Stack manipulation
BOOKMARK / GOTO   — Saved positions
FORK              — Parallel exploration
HYPERCARD-HIERARCHY — The room/card model

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

37.91%
按下载量换算32

Claude

28.74%
按下载量换算24

Cursor

18.9%
按下载量换算16

Gemini CLI

9.5%
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

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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