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planning规划

Agent Skill

planning 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

1,126

周安装

46

GitHub Stars

634

下载量

364
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:planning(规划)
来源仓库:https://github.com/awslabs/agent-plugins
仓库路径:skills/planning
安装命令:
npx skills add https://github.com/awslabs/agent-plugins --skill planning
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/awslabs/agent-plugins --skill planning

简介

实现动态规划以支持灵活的用户任务流程,能主动发现需求并提出适应性计划。

  • 包含脑暴阶段以确定所需技能和工具,避免强制固定工作流。
  • 第一阶段仅允许提出一个问题进行澄清,之后进入具体执行阶段。
  • 安装命令:npx skills add https://github.com/awslabs/agent-plugins --skill planning
  • planning 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Planning

Implements dynamic planning for flexible user journeys. Instead of forcing a rigid workflow, this skill discovers what the user wants, proposes a plan, and adapts as needed.


Phase 1: Brainstorming

Goal: Understand what the user wants to accomplish.

First message rules:

  • If the user describes a goal, ask one clarifying question at most — then move to Phase 2.
  • Do NOT list capabilities, pipeline steps, or menus unprompted.
  • Do NOT read files or run tools unless the user asks.

During brainstorming:

  • The goal of this phase is to determine which skills and tools to use to fulfill the user's intent. Every question you ask should help you decide whether a specific skill or tool belongs in the plan.
  • Before asking questions, review the name, description, and details of each skill in your context (do not actually load the full SKILL.md files yet), as well as the available MCP tools. Identify what information you'd need from the user to decide if each skill/tool is relevant.
  • Ask only questions whose answers would include or exclude a skill or tool from the plan. Do not ask generic or open-ended questions. Each question should map to a planning and skill-selection decision.
  • Do NOT ask the user about base model selection or preferences. Model selection is handled exclusively by the finetuning-setup skill.
  • When evaluating whether to include a skill, check if ALL of the skill's responsibilities are satisfied, not just the primary one. If a skill handles multiple decisions (e.g., technique selection AND model selection), include it if any of those decisions remain unresolved.
  • Move to Phase 2 as soon as you can determine which skills and tools the plan needs. Don't over-ask — 1 to 3 targeted questions should be sufficient in most cases.

Phase 2: Plan Generation

Goal: Propose a structured plan for the user to review.

Generate a plan as a numbered list of tasks. Each task has:

  • A short name
  • A one-sentence description of what happens
  • Which skill handles it (if applicable)

Format:

Based on what you've described, here's what I propose:

1. ⬜ **[Task Name]** — [What happens]. *(Skill: [skill-name])*
2. ⬜ **[Task Name]** — [What happens]. *(Skill: [skill-name])*
3. ⬜ **[Task Name]** — [What happens]. *(Skill: [skill-name])*

Does this plan look right, or would you like to change anything?

Rules for plan generation:

  • Before presenting a plan, always read references/skill-routing-constraints.md and validate the plan against it.
  • Draw tasks from the skills available in your context. Use each skill's name and description to determine relevance.
  • Only offer capabilities that are covered by an available skill. Do not offer, suggest, or imply the ability to help with tasks that no skill supports. If the user needs something outside the available skills, explain that it is not supported.
  • Not every plan needs every skill. Tailor the plan to the user's actual intent.
  • If the user already has artifacts (e.g., a trained model), skip the steps that produce them.
  • Keep plans short. Only include tasks that are necessary.

When the user approves the plan, write it to PLAN.md using the following format. Save the file under the project directory structure defined by the directory-management skill, if available.

# Plan

1. ⬜ **[Task Name]** — [Description]. _(Skill: [skill-name])_
2. ⬜ **[Task Name]** — [Description]. _(Skill: [skill-name])_
3. ⬜ **[Task Name]** — [Description]. _(Skill: [skill-name])_

Status indicators:

  • ⬜ Not Started
  • 🔄 In Progress
  • ✅ Completed

Update PLAN.md whenever a task's status changes.


Phase 3: Plan Iteration

Goal: Refine the plan until the user approves it.

  • If the user suggests changes, regenerate the plan incorporating their feedback.
  • If the user approves (e.g., "looks good", "let's go", "yes"), begin execution by handing off to the first task's skill.

Execution

Once the plan is approved:

  1. Before starting a task, update its status in PLAN.md to 🔄 (In Progress).
  2. If the task maps to a skill, load that skill's full SKILL.md before doing any work. Do not attempt the task from general knowledge — always defer to the skill's instructions.
  3. Execute the task by following the loaded skill's workflow.
  4. When the task completes, update its status in PLAN.md to ✅ (Completed), then briefly confirm completion and move to the next task.
  5. If the user interrupts with a new request mid-execution:

- Completed tasks are immutable — DO NOT ever modify completed tasks in the plan. You are allowed to only modify tasks that are in progress or not started. - Regenerate the remaining tasks to incorporate the user's new input. - Present the updated remainder for approval before continuing.


Plan Completion

When all tasks in the plan are done:

"We've completed everything in the plan. What would you like to do next?"

This re-enters Phase 1 (Brainstorming) for a new goal. There is no terminal state — the conversation continues as long as the user wants.


References

Always load the corresponding reference plan based on the customer intent to learn about what a typical plan looks like, and then adjust based on customer's needs.

  • references/model-customization-plan.md — A typical end-to-end model customization/finetuning plan for reference when generating plans.
  • references/skill-routing-constraints.md — Mandatory inclusion rules, ordering constraints, and skill boundary rules. Always consult when generating or modifying a plan.

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

34.6%
按下载量换算126

Claude

34.19%
按下载量换算124

Cursor

19.23%
按下载量换算70

Gemini CLI

9.22%
按下载量换算34

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

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/awslabs/agent-plugins --skill planning 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。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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