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context-driven-development情境驱动的开发

Agent Skill

context-driven-development 用于查找、检索和筛选相关信息,适合在 Local Agent 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

198

周安装

8

下载量

62
Local Agent

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。

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:context-driven-development(情境驱动的开发)
来源仓库:https://skills.volces.com
仓库路径:context-driven-development
安装命令:
OpenClaw / Moltbot / Clawbot
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 对应宿主 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.sh安装方式未标明
OpenClaw / Moltbot / Clawbot

简介

用于查找、检索和筛选相关信息。context-driven-development 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

  • 适合在 Local Agent 中根据关键词快速定位候选结果。
  • 可结合来源仓库和原始 README 继续核验具体用法。
  • 安装前建议确认权限范围和维护状态,避免触发联网或命令执行。
  • 注意维护状态,确保技能仍处于可用阶段。

SKILL.md

Context-Driven Development

Treat project context as a first-class artifact managed alongside code. Instead of relying on ad-hoc prompts or scattered documentation, establish a persistent, structured foundation that informs all AI interactions.

Installation

OpenClaw / Moltbot / Clawbot

npx clawhub@latest install context-driven-development

WHAT This Skill Does

Creates and maintains a set of context documents that:

  • Define what you're building and why (product.md)
  • Specify technology choices and constraints (tech-stack.md)
  • Establish how the team works (workflow.md)
  • Track what's happening (tracks.md)

WHEN to Use

Use for:

  • Setting up new projects with AI-assisted development
  • Onboarding team members to existing codebases
  • Ensuring consistent AI behavior across sessions
  • Documenting decisions that affect code generation
  • Managing projects with multiple contributors or AI assistants

Skip for:

  • Solo experiments or throwaway prototypes
  • Single-file scripts
  • Projects without AI assistance

Keywords: context, project setup, documentation, AI alignment, team workflow, product vision, tech stack

Core Philosophy

Context precedes code.
Living documentation.
Single source of truth.
AI alignment.
  1. Context precedes code — Define what you're building and how before implementation
  2. Living documentation — Context artifacts evolve with the project
  3. Single source of truth — One canonical location for each type of information
  4. AI alignment — Consistent context produces consistent AI behavior

The Workflow

Context → Spec & Plan → Implement
  1. Context Phase: Establish or verify project context artifacts exist and are current
  2. Specification Phase: Define requirements and acceptance criteria for work units
  3. Planning Phase: Break specifications into phased, actionable tasks
  4. Implementation Phase: Execute tasks following established workflow patterns

The Context Documents

product.md — WHAT and WHY

Purpose: Captures product vision, goals, target users, and business context.

Contents:

  • Product name and one-line description
  • Problem statement and solution approach
  • Target user personas
  • Core features and capabilities
  • Success metrics and KPIs
  • Product roadmap (high-level)

Update when:

  • Product vision or goals change
  • New major features are planned
  • Target audience shifts

tech-stack.md — WITH WHAT

Purpose: Documents technology choices, dependencies, and architectural decisions.

Contents:

  • Primary languages and frameworks
  • Key dependencies with versions
  • Infrastructure and deployment targets
  • Development tools and environment
  • Testing frameworks
  • Code quality tools

Update when:

  • Adding new dependencies
  • Upgrading major versions
  • Changing infrastructure
  • Adopting new tools or patterns

workflow.md — HOW to Work

Purpose: Establishes development practices, quality gates, and team workflows.

Contents:

  • Development methodology (TDD, trunk-based, etc.)
  • Git workflow and commit conventions
  • Code review requirements
  • Testing requirements and coverage targets
  • Quality assurance gates
  • Deployment procedures

Update when:

  • Team practices evolve
  • Quality standards change
  • New workflow patterns are adopted

tracks.md — WHAT'S HAPPENING

Purpose: Registry of all work units with status and metadata.

Contents:

  • Active tracks with current status
  • Completed tracks with completion dates
  • Track metadata (type, priority, assignee)
  • Links to individual track specs

Update when:

  • New work starts
  • Work status changes
  • Work completes

Directory Structure

context/
├── product.md            # Product vision and goals
├── tech-stack.md         # Technology choices
├── workflow.md           # Development practices
├── tracks.md             # Work unit registry
└── styleguides/          # Language-specific conventions
    ├── python.md
    ├── typescript.md
    └── ...

Setup: New Project (Greenfield)

For new projects, create all artifacts from scratch:

  1. Create context/product.md:

- Define the problem you're solving - Describe target users - List core features for v1 - Define success metrics

  1. Create context/tech-stack.md:

- Choose languages and frameworks - Document key dependencies with versions - Specify infrastructure targets - List development tools

  1. Create context/workflow.md:

- Define branching strategy - Set commit conventions - Establish testing requirements - Document deployment process

  1. Create context/tracks.md:

- Start with empty registry - Add work units as they're created

Setup: Existing Project (Brownfield)

For existing codebases, extract context from what exists:

  1. Analyze the codebase:

- Read package.json, requirements.txt, go.mod, etc. - Look at existing README and docs - Check git history for patterns

  1. Create context/tech-stack.md:

- Document discovered dependencies - Note infrastructure from configs (Docker, CI, etc.)

  1. Create context/product.md:

- Infer product purpose from code - Document current feature set - Note any README content

  1. Create context/workflow.md:

- Document existing practices - Note any established patterns

Maintenance Principles

Keep Artifacts Synchronized

Changes in one artifact should reflect in related documents:

  • New feature in product.md → Update tech-stack.md if new dependencies needed
  • Completed track → Update product.md to reflect new capabilities
  • Workflow change → Update all affected track plans

Update tech-stack.md When Adding Dependencies

Before adding any new dependency:

  1. Check if existing dependencies solve the need
  2. Document the rationale for new dependencies
  3. Add version constraints
  4. Note any configuration requirements

Verify Context Before Implementation

Before starting any work:

  1. Read all context artifacts
  2. Flag any outdated information
  3. Propose updates before proceeding
  4. Confirm context accuracy

Validation Checklist

Before starting implementation, validate:

Product Context:

  • product.md reflects current vision
  • Target users are accurately described
  • Feature list is up to date

Technical Context:

  • tech-stack.md lists all current dependencies
  • Version numbers are accurate
  • Infrastructure targets are correct

Workflow Context:

  • workflow.md describes current practices
  • Quality gates are defined
  • Commit conventions are documented

Anti-Patterns

Anti-PatternProblemFix
Stale ContextDocuments become outdated and misleadingUpdate context as part of each track's completion
Context SprawlInformation scattered across multiple locationsUse defined artifact structure; resist new document types
Implicit ContextRelying on knowledge not captured in artifactsIf referenced repeatedly, add to appropriate artifact
Over-SpecificationContext so detailed it's impossible to maintainKeep focused on decisions affecting AI behavior and team alignment

Session Continuity

Starting a New Session

  1. Read context/product.md to orient yourself
  2. Check context/tracks.md for active work
  3. Read relevant track specs for current task
  4. Verify context artifacts are current

Ending a Session

  1. Update track status with current progress
  2. Note any blockers or decisions made
  3. Commit in-progress work with clear status
  4. Update tracks.md if status changed

Benefits

Team Alignment:

  • New team members onboard faster with explicit context
  • Consistent terminology across the team
  • Shared understanding of product goals

AI Consistency:

  • AI assistants produce aligned outputs across sessions
  • Reduced need to re-explain context
  • Predictable behavior based on documented standards

Institutional Memory:

  • Decisions and rationale are preserved
  • Context survives team changes
  • Historical context informs future decisions

NEVER Do

  1. NEVER start implementation without reading context — context precedes code
  2. NEVER add dependencies without updating tech-stack.md — keep the source of truth current
  3. NEVER let context documents get stale — update them as part of completing work
  4. NEVER scatter context across ad-hoc documents — use the defined structure
  5. NEVER assume AI remembers previous sessions — context must be in artifacts
  6. NEVER skip context for "quick" changes — small changes compound into drift

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

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

Local Agent

90.93%
按下载量换算56

安全审计

暂无安全审计结果可展示。

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

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来源信息

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