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ai-context-generatorAI 上下文生成器

Agent Skill

ai-context-generator 用于补充开发相关能力,适合在 OpenClaw 中需要让 Agent 承接开发相关任务时使用。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。

总安装

2,421

周安装

97

GitHub Stars

公开资料未说明

下载量

784
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:ai-context-generator(AI 上下文生成器)
来源仓库:https://github.com/sopaco/ai-context-generator
安装命令:
openclaw skills install ai-context-generator
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 ai-context-generator

简介

为编码代理生成 .ai-context 知识库,提升开发效率。

  • 适用于新建 AI 辅助开发项目或创建项目时自动激活。
  • 可结合项目代码和需求生成结构化上下文文档。
  • 安装命令:openclaw skills install ai-context-generator。
  • 建议确认是否会触发联网、命令执行或文件读写操作。

SKILL.md

name
ai-context-generator
description
|

AI Context Generator

A reusable skill for creating project knowledge bases that help coding agents work faster and smarter.

🎯 When to Use This Skill

Activate when:

  • Setting up a new project for AI-assisted development
  • User requests: "create ai-context", "setup project knowledge", "generate .ai-context"
  • Existing .ai-context is outdated and needs regeneration
  • After major project restructuring

Do NOT activate when:

  • Project already has fresh .ai-context (check SKILL.md date)
  • User asks for unrelated documentation
  • Simple code tasks with clear existing context

📋 What This Skill Generates

Creates a .ai-context/ directory with:

.ai-context/
├── SKILL.md                    # Entry point with activation rules
├── DYNAMICS.md                 # Active issues & constraints (Dynamic)
├── references/
│   ├── PROJECT-ESSENCE.md      # What & why (High stability)
│   ├── ARCHITECTURE.md         # Component relationships (Medium stability)
│   └── DECISIONS.md            # Design decisions (Update on change)
└── meta/
    ├── MAINTENANCE.md          # How to maintain this knowledge
    ├── templates/              # (Optional) Custom templates
    └── scripts/                # (Optional) Maintenance scripts

Stability Tiers

TierFileUpdate FrequencyToken Budget
0PROJECT-ESSENCE.mdQuarterly / Major version~500 tokens
1ARCHITECTURE.mdMonthly / Sprint~1000 tokens
2DECISIONS.mdPer decision change~800 tokens
3DYNAMICS.mdAs needed (issues)~600 tokens

🔧 Generation Process

Step 1: Gather Project Intelligence

Before generating, collect:

□ Read AGENTS.md (if exists) — operational rules
□ Read README.md — user-facing description
□ Read package.json — dependencies, scripts, entry points
□ Scan directory structure — identify components
□ Read docs/ or litho.docs/ — existing documentation
□ Identify key source files — main entry points
□ Note technology stack — frameworks, languages, platforms

Step 2: Extract Knowledge

For PROJECT-ESSENCE.md:

  • What is this project? (one sentence)
  • Why does it exist? (problem/solution)
  • Who is it for? (target users)
  • What does it provide? (key features)
  • Core constraints? (security, compatibility)

For ARCHITECTURE.md:

  • System diagram (ASCII or Mermaid)
  • Component responsibilities
  • Data flow between components
  • Key dependencies
  • Important patterns

For DECISIONS.md:

  • Non-obvious design choices
  • Trade-offs made
  • Constraints accepted
  • Decisions that might be revisited

For DYNAMICS.md:

  • Current blockers
  • Known workarounds
  • Temporary constraints
  • Recently resolved issues (brief)

Step 3: Generate Files

Use templates from templates/ directory:

  1. Start with SKILL.md — entry point with activation rules
  2. Generate references/PROJECT-ESSENCE.md — core identity
  3. Generate references/ARCHITECTURE.md — component map
  4. Generate references/DECISIONS.md — design rationale
  5. Generate DYNAMICS.md — active issues
  6. Generate meta/MAINTENANCE.md — upkeep guide

Step 4: Validate Quality

□ SKILL.md has clear activation triggers
□ PROJECT-ESSENCE.md readable in 2 minutes
□ ARCHITECTURE.md shows big picture (no code)
□ DECISIONS.md justified with rationale
□ DYNAMICS.md only contains current issues
□ All files dated at top
□ Total token budget < 4000 tokens

📝 Writing Principles

Do:

  • ✅ Write for someone who knows nothing about the project
  • ✅ Use diagrams over paragraphs
  • ✅ Focus on "why" not "how"
  • ✅ Keep files under 150 lines each
  • ✅ Link between related sections
  • ✅ Include "Last updated" dates

Don't:

  • ❌ Copy-paste code snippets (link to files instead)
  • ❌ Document every file/function
  • ❌ Include details that change frequently
  • ❌ Duplicate content across files
  • ❌ Use jargon without context

🔄 Integration with AGENTS.md

AGENTS.md = "How to work" (commands, style, rules)
.ai-context = "What the project is" (architecture, decisions, issues)

Both should be read at session start. They serve different purposes and should not overlap.


📚 Template Reference

Templates are provided in templates/:

TemplatePurpose
skill.md.tmplSKILL.md with placeholder prompts
essence.md.tmplPROJECT-ESSENCE.md structure
architecture.md.tmplARCHITECTURE.md with diagram prompts
decisions.md.tmplDECISIONS.md with ADR format
dynamics.md.tmplDYNAMICS.md with status tracking
maintenance.md.tmplMAINTENANCE.md guide

🛠️ Automation Scripts

Scripts in scripts/ can help with:

ScriptPurpose
generate.tsInteractive generation from templates
check-drift.tsCompare documented vs actual structure
audit-dynamics.tsFlag stale issues (>30 days)

💡 Example Usage

User: "Setup ai-context for my project"

Agent:

  1. Activate this skill
  2. Read AGENTS.md, README.md, package.json
  3. Scan directory structure
  4. Generate each file using templates
  5. Ask clarifying questions if needed:

- "What's the main problem this project solves?" - "Any non-obvious design decisions I should know about?" - "Current blockers or workarounds?"


⚠️ Important Notes

  • Generated knowledge is a starting point, not final truth
  • Agent should verify against actual code during first session
  • User should review generated content for accuracy
  • Schedule regular audits (monthly recommended)

📖 References


*This skill creates knowledge bases optimized for AI agents. For questions or improvements, see MAINTENANCE.md.*

适合场景

01

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

04

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

82.96%
按下载量换算650

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

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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