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研究检索执行命令github未标认证来源可访问许可证需确认审计提醒

create-prompt-plan创建即时计划

Agent Skill

用于辅助提示词、系统指令、Agent 行为约束和工作流模板的整理。它适合让 Agent 规范任务边界、统一输出格式、拆分操作步骤或优化提示词可复用性。使用时需要保留真实业务约束,不要把示例当硬规则;涉及自动执行、外部工具或高风险操作时,应在提示词中明确确认步骤、权限边界和失败处理方式。

总安装

549

周安装

17

GitHub Stars

292

下载量

140
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:create-prompt-plan(创建即时计划)
来源仓库:https://github.com/tobihagemann/turbo
仓库路径:skills/create-prompt-plan
安装命令:
npx skills add https://github.com/tobihagemann/turbo --skill create-prompt-plan
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/tobihagemann/turbo --skill create-prompt-plan

简介

将规范分解为可执行的独立提示词任务单元。create-prompt-plan 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

  • 适用于大型项目分阶段实施和提示词模块化设计。
  • 自动生成 .turbo/prompts.md 文件,保留业务约束条件。
  • 安装需确认 spec 文件路径和输出目录结构。
  • 涉及高风险操作时应明确权限边界和失败处理机制。

SKILL.md

Create Prompt Plan

Read a specification file and decompose it into a series of implementation prompts. Each prompt represents one unit of work for a separate Claude Code session. Save the output to .turbo/prompts.md.

General skill assignment happens later by /pick-next-prompt when each prompt is planned for implementation. However, if the spec implies domain-specific skills, mention those specific skills in the prompt text as hints.

Step 1: Read the Spec

Read the spec file. Default location: .turbo/spec.md. Accept a different path if provided by the user.

Identify:

  • Scope — total surface area of work
  • Work categories — UI, backend, data layer, infrastructure, tests, documentation, tooling
  • Dependencies — which pieces must exist before others can start
  • Greenfield vs existing — is there an established codebase to work within

Step 2: Decompose Into Prompts

Split the spec into prompts where each prompt fits a single Claude Code context session.

Sizing

  • One prompt = one logical unit of work (a feature, a subsystem, a layer)
  • Never split tightly-coupled pieces across prompts (if UI + API + tests are inseparable, keep them together)
  • Split independent subsystems into separate prompts
  • If a prompt would touch more than ~15-20 files or span 3+ unrelated subsystems, split further
  • If the entire scope fits one session, produce a single prompt
  • Each prompt must leave the codebase fully integrated, with no components unreachable from the project's entry points

Ordering

Order by dependency, foundational work before dependent work:

  1. Setup and scaffolding (project init, config, CI)
  2. Data and domain layer (models, schemas, types)
  3. Core business logic
  4. API and service layer
  5. UI and frontend
  6. Integration and end-to-end concerns

Status tracking

Each prompt gets a status: pending, in-progress, done.

Step 3: Write.turbo/prompts.md

Create the .turbo/ directory if it does not exist. Write the output using this format:

# Prompt Plan: [Project/Feature Name]

Source: `.turbo/spec.md`
Generated: [date]
Total prompts: N

---

## Prompt 1: [Descriptive Title]
**Status:** pending
**Context:** [What state the project is in before this session starts]
**Depends on:** none

### Prompt

[What to build — specific files, features, acceptance criteria. What "done" looks like — tests passing, endpoints working, etc. Reference to spec sections if helpful.]


---

## Prompt 2: [Descriptive Title]
**Status:** pending
**Context:** [What prior prompts built that this one depends on]
**Depends on:** Prompt 1

### Prompt

[What to build...]

Step 4: Review Against Spec

After writing, spawn a subagent (model: "opus", do not set run_in_background) to review the prompt plan against the source spec. The subagent should:

  1. Read references/prompt-plan-reviewer.md for review guidelines
  2. Read the prompt plan (.turbo/prompts.md) and the source spec in full
  3. Produce a review report following the format in the guidelines

After the subagent returns its review report, run /evaluate-findings on the recommendations to triage issues and apply fixes to .turbo/prompts.md.

Step 5: Present Summary

After writing and verification, present a brief summary: number of prompts, one-line description of each prompt's scope, and any assumptions made about ambiguities.

Rules

  • Never merge setup and finalization into the same prompt
  • If the spec is ambiguous about what belongs together, split conservatively (smaller prompts are safer than oversized ones)
  • Each prompt must be self-contained with enough context to understand the work without reading the full spec
  • The .turbo/prompts.md file is the only output — do not modify the spec or project files

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

37.04%
按下载量换算52

Claude

26.68%
按下载量换算37

Cursor

18.02%
按下载量换算25

Gemini CLI

8.32%
按下载量换算12

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/tobihagemann/turbo --skill create-prompt-plan 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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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