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staged-task-execution阶段性任务执行

Agent Skill

staged-task-execution 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

公开资料未说明

下载量

86
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:staged-task-execution(阶段性任务执行)
来源仓库:https://github.com/proladon/agent-vault
仓库路径:skills/staged-task-execution
安装命令:
npx skills add https://github.com/proladon/agent-vault --skill staged-task-execution
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/proladon/agent-vault --skill staged-task-execution

简介

staged-task-execution 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词或任务场景快速定位候选结果时使用。

  • 适用于研究检索类任务,支持基于来源线索和仓库路径进行信息聚合与过滤。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装,需结合原始 README 确认具体用法。
  • 安装前建议核实权限范围、维护状态,并注意是否涉及联网、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

Staged Task Execution

Purpose

Break large requirements into small, atomic tasks. Execute one task at a time. Track state and context in the project's temp/ folder so work can be paused and resumed safely.

Announce at start: "I'm using the staged-task-execution skill to plan and track this work."


When to Use This Skill

Trigger this workflow when any of the following is true:

  • The request involves changes to more than 2-3 files
  • The requirement has multiple distinct phases (e.g., API → store → component)
  • The work could take more than one exchange to complete
  • The task involves creating new views, new features, or significant refactoring
  • The user uses any of the following trigger phrases:

English: "step by step", "staged", "one at a time", "don't rush", "large feature", "big change", "don't do everything at once", "large scope", "many changes", "confirm before continuing"

中文: 「分步執行」、「逐步完成」、「一步一步」、「分階段」、「大功能」、「大改動」、「不要一次做完」、「慢慢來」、「確認後再繼續」、「按步驟」、「逐一確認」、「分批執行」

Resume triggers — English: "continue where we left off", "resume", "pick up from last task", "keep going", "what's next"

Resume triggers — 中文: 「繼續上次」、「繼續執行」、「繼續做」、「從上次繼續」、「接著做」、「繼續進行」、「繼續下一步」、「繼續完成」

⚠️ Important: 「繼續完成 」means resume the workflow from the last pending task — it does NOT mean auto-complete all remaining tasks. Step 7 (user confirmation between each task) still applies.

Resume: Continue a Previous Session

If the user asks to resume or continue a previous task (using any resume trigger phrase above), do not start a new plan. Instead:

  1. Locate the session folder: Search temp/ for folders containing a progress.md file. If the user mentioned a specific feature name, look for that folder; otherwise list all candidates and ask the user which one to resume.
  2. Read progress.md: Understand the current status, completed tasks, key decisions, and what the next step is.
  3. Read tasks.md: Identify which tasks are done ([x]) and which remain ([]).
  4. Summarize state to user: Briefly report:

- Feature name - How many tasks are done vs. total - What the next pending task is

  1. Ask for confirmation before executing the next task — use the same vscode_askQuestions prompt from Step 7.
  2. Continue from the next pending task — proceed with Step 5 as normal.
Do NOT re-run completed tasks. Do NOT recreate the session folder or overwrite existing tasks.md / progress.md. ⚠️ Even if the user used a phrase like 「繼續完成」, this does not grant permission to skip Step 7 confirmations. Step 7 is mandatory after every single task, including during resume.

Step 1: Assess & Plan

Before writing any code, analyze the full scope of the requirement:

  1. Read relevant existing files to understand the current state
  2. Decompose the requirement into small, atomic tasks — each task should be completable in a single focused effort (one component, one API endpoint, one store module, etc.)
  3. Order tasks by dependency (foundational work first)
  4. Identify which tasks are blocking others

Step 2: Create the Session Folder

Create a folder in temp/ named after the feature using kebab-case:

temp/<feature-name>/
├── tasks.md
├── progress.md
└── references/
    ├── spec.md
    ├── backend.md
    └── ...others

temp/archive/                  ← completed features are moved here
└── <feature-name>/

skills/staged-task-execution/scripts/
├── setup.py                   ← creates the session folder structure
└── archive.py                 ← moves a completed feature to temp/archive/

Naming convention: Use a short English kebab-case description of the feature (e.g., member-point-exchange, ai-campaign-push, device-info-panel).

Use the setup script to create the folder and empty stub files in one step:

python skills/staged-task-execution/scripts/setup.py <feature-name>

References folder: Create a references/ subfolder and immediately copy all user-provided materials into it:

  • If the user attached or linked a spec file (e.g., from specBook/), copy its full content into references/spec.md
  • If the user provided backend API docs, schemas, or endpoint lists, copy them into references/backend.md
  • If the user provided any other reference material (Figma descriptions, migration notes, existing code excerpts), copy each into an appropriately named file under references/
  • If no material was provided for a category, skip that file — do not create empty placeholders

Common reference files:

  • spec.md — functional spec, product requirements, or specBook content
  • backend.md — backend API endpoints, request/response schemas, authentication notes
  • Any other reference material (e.g., figma.md, existing-api.md, migration-notes.md)

These files are read-only reference material — they describe what to build, not the implementation plan.


Step 3: Write tasks.md

Format:

# Tasks: [Feature Name]

## Overview

[1-2 sentence summary of what this work accomplishes]

## Task List

- [ ] 1. [Task Name] — [one-line description]
- [ ] 2. [Task Name] — [one-line description]
- [ ] 3. [Task Name] — [one-line description]
     ...

## Task Details

### 1. [Task Name]

**Files:** `src/path/to/file.vue`, `src/api/module.js`
**What to do:** [Detailed description of what this task involves]
**Dependencies:** None / Task N

### 2. [Task Name]

...

Rules for tasks:

  • Each task touches a single concern (one API function, one component, one store module)
  • Tasks must be independently verifiable — you can tell when one is done
  • Avoid tasks like "implement feature X" — split into "create API", "add store module", "build component"

Step 4: Write progress.md

Format:

# Progress: [Feature Name]

## Status

**Current:** Task [N] of [Total] — [Task Name]
**Last Updated:** [date]

## Context & Background

[Key facts about the existing codebase relevant to this work. API patterns used, store structure, component conventions, etc.]

## Completed Tasks

[Empty initially — fill in as tasks are completed]

## Active Task

**Task [N]: [Name]**
[What is currently being worked on]

## Key Decisions

[Design decisions made, patterns chosen, deviations from standard approach — anything a future agent needs to know]

## Files Modified

[List of files changed so far]

## Next Step

[What should happen next]

Step 5: Execute One Task

  1. Announce which task is starting: "Starting Task N: [Name]"
  2. Implement only that task — do not work ahead
  3. Follow all project coding standards from instructions files
  4. After completing the task implementation, verify no obvious errors
  5. Always proceed to Step 6 → Step 7. Never skip to the next task automatically.

Step 6: Update files after each task

After completing a task:

  1. Update tasks.md: Mark the completed task with [x]
  2. Update progress.md:

- Move task to "Completed Tasks" with a brief note on what was done - Update "Current" status to next task - Add any files modified - Record any decisions made - Update "Next Step"


Step 7: Ask User to Continue ⚠️ MANDATORY

This step is NON-NEGOTIABLE. You MUST stop and ask the user before proceeding to the next task. Do NOT auto-continue, do NOT skip this step, do NOT start the next task without explicit user confirmation.

Use the vscode_askQuestions tool to ask:

header: "Continue?"
question: "Task N complete: [Task Name]. Ready to proceed to Task N+1: [Next Task Name]?"
options:
  - label: "Yes, continue"       (recommended: true)
  - label: "No, pause here"
  - label: "Skip to a different task"
  - label: "Adjust the plan first"
allowFreeformInput: true

If user says yes: Proceed to Step 5 with the next task. If user says no/pause: Save all state to progress.md, confirm to user where context is saved, and stop. If user says skip: Ask which task they want to jump to, update progress.md, then execute. If user wants to adjust: Update tasks.md with the revised plan, confirm the new plan with the user, then continue.


Step 8: Completion

When all tasks are marked [x] in tasks.md:

  1. Update progress.md status to "Completed"
  2. Archive the feature folder by running the archive script: python skills/staged-task-execution/scripts/archive.py <feature-name> This moves temp/<feature-name>/ to temp/archive/<feature-name>/.
  3. Notify the user: "All [N] tasks complete. Session context archived to temp/archive/<feature-name>/."
  4. Optionally summarize what was built/changed

File Lifecycle

The temp/ folder is a working scratchpad — files there are not committed by default.

  • temp/<feature-name>/ — active session folder, created by setup.py
  • temp/archive/<feature-name>/ — completed sessions, moved here automatically by Step 8 via archive.py

The user may choose to delete the temp/ folder entirely or keep the archive for future reference.


Example Folder Names

ScenarioFolder Name
AI campaign push featuretemp/ai-campaign-push/
Member point exchange recordstemp/member-point-exchange/
Refactor FeatureKeyDebuggertemp/feature-key-debugger-refactor/
Device info paneltemp/device-info-panel/
Custom field sub-optionstemp/custom-field-sub-options/

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

34.54%
按下载量换算30

Claude

30.92%
按下载量换算27

Cursor

16.97%
按下载量换算15

Gemini CLI

8.96%
按下载量换算8

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。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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