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featureplanningautopilotfeatureplanningautopilot 开发

Agent Skill

featureplanningautopilot 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。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。

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7,854

周安装

324

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下载量

2,566
OpenClaw

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

MIT-0

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:featureplanningautopilot(featureplanningautopilot 开发)
来源仓库:https://github.com/naname-zz/featureplanningautopilot
安装命令:
openclaw skills install featureplanningautopilot
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install featureplanningautopilot

简介

featureplanningautopilot 用于在编码前自动生成可执行的功能开发计划。

  • 支持将模糊需求转化为分阶段、可验证的任务分解结构。
  • 输出包含验收标准、技术选型建议与风险评估的完整方案文档。
  • 强调迭代交付,每阶段产出物均需明确验证方式与反馈入口。
  • 适用于敏捷开发流程,但不替代产品经理对需求的最终定义权。

SKILL.md

name
Feature Planning AutoPilot
description
A general-purpose feature development planning skill. Used to generate executable, verifiable, and iterative development plans before coding, and to automatically capture lessons learned after each conversation.
license
MIT

Feature Planning AutoPilot

This Skill standardizes the "analyze first → plan next → implement last" approach. It applies to frontend, backend, full-stack, API integration, SQL migrations, and mobile page refactoring tasks.

1) When to Use

Activate this Skill when the user expresses any of the following intentions:

  • "Analyze before writing code"
  • "Give me a plan first" / "Break it into steps" / "Execute in phases"
  • "Ensure correctness and feasibility"
  • "Create a reusable implementation blueprint"

2) Expected Outputs

Every planning session must produce the following four deliverables:

  1. Scope Definition: Clearly state what is and is not included in this task.
  2. Execution Plan: 3–9 verifiable steps in clear sequence.
  3. Risks & Rollback: Key risk points and a minimal rollback strategy.
  4. Acceptance Checklist: Actionable verification items (APIs, pages, logs, builds, tests).

3) Standard Workflow (Must Follow in Order)

Phase A – Quick Clarification

  • Restate the goal in 1–2 sentences
  • Confirm constraints: tech stack, directory, whether API/DB changes are allowed, timeline
  • If information is missing: ask at most 1–3 key questions; default when possible

Phase B – Context Scan

Complete at minimum the following checks before producing a plan:

  • Location of relevant pages / APIs / services
  • Data sources and state transitions (e.g., Pending Delivery → Pending Inbound → Completed)
  • Existing similar implementations (prefer reuse)
  • List of files likely to be affected

Phase C – Plan Drafting

Plan requirements:

  • 3–9 steps, each with a concise 3–7 word action title
  • Every step must be verifiable (has a "definition of done")
  • Only 1 step may be in-progress at a time
  • State prerequisites for external dependencies or database changes

Phase D – Implementation & Validation

  • Execute the plan step by step; update status after each step
  • Perform at least one local validation per phase
  • Before finishing, run a minimum viable acceptance check (build / key path click-through / API response)

Phase E – Lessons Captured (Auto-Iterate)

At the end of the conversation, append three categories of experience to evolution.json:

  • preferences: User's preferred output style or delivery format
  • fixes: Issues encountered this session and how they were resolved
  • custom_prompts: Strong prompts that can be reused directly next time

Also sync the learnings back into the "Experience Enhancements" section of SKILL.md.

4) Plan Template (Ready to Reuse)

## Feature Development Plan (AutoPilot)

### 0. Goal & Scope
- Goal:
- Included in this task:
- Excluded from this task:
- Prerequisites:

### 1. Execution Steps
1. [ ] Review current state and dependencies
   - Definition of done: Relevant files and data flow located
2. [ ] Design minimal-change solution
   - Definition of done: Modification points and impact surface confirmed
3. [ ] Implement core changes
   - Definition of done: Core path code complete
4. [ ] Handle edge cases and errors
   - Definition of done: Empty state / failure state / permission state all functional
5. [ ] Verify and regression test
   - Definition of done: Key paths pass, results are reproducible

### 2. Risks & Rollback
- Risk:
- Monitoring signal:
- Rollback method:

### 3. Acceptance Criteria
- [ ] Feature behavior matches requirements
- [ ] No new build errors introduced
- [ ] Key UI / API paths verified

5) High-Quality Plan Rules (Hard Constraints)

  • No "hollow steps" (e.g., "implement feature")
  • Never omit "data source" or "state transitions"
  • No unrelated large-scale changes (only minimal changes relevant to the task)
  • Never skip validation (at least one local check + one result check)
  • Never overstate conclusions (explicitly say so when something cannot be verified)

6) Common Task Mappings

A. Mobile Page Optimization

Must include:

  • Visual layer (spacing, overflow, readability, tap target size)
  • Interaction layer (default state, disabled state, loading state, empty state)
  • Data layer (API fields consistent with rendered output)

B. List / Stats Consistency

Must include:

  • Confirm same source API
  • Confirm same filtering criteria
  • Verify homepage numbers match detail list

C. State-Driven Workflows (e.g., Inbound)

Must include:

  • Define initial state
  • Define conditions that trigger state transitions
  • Intercept and prompt for invalid states

7) Auto-Iteration Protocol

Trigger an experience update for this Skill when any of the following conditions are met:

  • User explicitly responds with "this is great" or "this isn't working"
  • A build error occurs and is resolved
  • A deviation between the plan and the actual implementation is corrected

Update Structure

evolution.json follows this structure:

{
  "last_updated": "ISO_DATETIME",
  "preferences": [],
  "fixes": [],
  "custom_prompts": ""
}

Principles for Writing Learnings

  • Preferences → write abstract rules (reusable across projects)
  • Fixes → write "trigger condition + resolution approach"
  • Prompts → write instructions that can be pasted directly

8) Recommended Trigger Commands

  • /plan-auto — Generate a standard execution plan
  • /plan-auto deep — Output a full plan including risks and rollback
  • /plan-auto mobile — Focus on mobile page and interaction refactoring
  • /plan-auto evolve — Automatically capture learnings at the end of the session

9) Experience Enhancements (Synced from evolution.json)

This section is auto-updated by the iteration process to prevent experience loss.

User-Learned Best Practices & Constraints

  • Plan conclusions must align with the current implementation scope; avoid overreaching beyond applicable scenarios.
  • Before presenting an implementation plan, cross-check existing code and database state to ensure the plan is logically sound and actionable.
  • Before outputting a plan, clearly define the applicable scope and state transition conditions, and state all necessary prerequisites.

适合场景

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OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

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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

补充不同宿主或平台的使用分布数据

能力 5

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

OpenClaw

98.92%
按下载量换算2,538

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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。

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