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context-engineering情境工程

Agent Skill

context-engineering 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

186

周安装

8

GitHub Stars

公开资料未说明

下载量

65
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

MIT

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-engineering(情境工程)
来源仓库:https://github.com/doubleslashse/claude-marketplace
仓库路径:skills/context-engineering
安装命令:
npx skills add doubleslashse/claude-marketplace --skill "context-engineering"
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。

AgentSkills.tonpx skills
npx skills add doubleslashse/claude-marketplace --skill "context-engineering"

简介

发现并安装 AI 代理的技能,扩展智能助手的功能边界。

  • 适用于在 Codex、Claude、Cursor、Gemini CLI 中动态增强 Agent 能力。
  • 通过关键词匹配任务场景,自动检索并集成合适的技能模块。
  • 安装前需验证来源仓库权限,避免执行不可信代码或访问敏感数据。
  • 部分技能可能涉及联网、文件读写或命令执行,请谨慎授权。

SKILL.md

name
context-engineering
description
Context window management techniques for maintaining efficiency and preventing context bloat
triggers

Context Engineering Skill

This skill provides techniques for managing context effectively throughout the workflow to prevent bloat and maintain efficiency.

Core Principles

  1. Stay Under 40%: Orchestrator should never exceed 40% context usage
  2. Fresh Context Per Task: Each major task gets a fresh agent with clean context
  3. Load Only What's Needed: Don't load full files when summaries suffice
  4. Delegate Deep Work: Spawn agents for context-heavy operations

Context Budget Guidelines

RoleContext BudgetReason
Orchestrator<40%Needs room for coordination
Interviewer<70%Conversation history accumulates
Planner<60%Needs to see requirements + codebase patterns
Executor<80%Can focus on single task deeply
Verifier<60%Needs to cross-reference requirements and code

Context Loading Strategies

Selective Loading

Instead of loading full files:

BAD: Read entire codebase
GOOD: Read specific files needed for current task
BEST: Read summaries, then specific sections

Hierarchical Loading

Load context in layers:

  1. L1 Summary: High-level overview (FLOW.md)
  2. L2 Details: Item-specific state (ITEM-XXX.md)
  3. L3 Specifics: Task-specific files (only files in current task)

Incremental Loading

Load more context only when needed:

1. Start with minimal context
2. Identify what's missing
3. Load specific missing pieces
4. Repeat as needed

Fresh Context Patterns

When to Use Fresh Context

Spawn a fresh agent when:

  • Starting a new task in EXECUTE phase
  • Moving to a new phase
  • Current context is getting heavy
  • Deep codebase exploration needed

Fresh Context Handoff

When spawning fresh agent:

Include in handoff:
- Task ID and definition
- Key decisions from ITEM-XXX.md
- Relevant file paths
- Success criteria

Exclude:
- Full conversation history
- Files not related to task
- Exploration paths not taken

Context Reset Points

Natural points to reset context:

  • Phase transitions
  • After each completed task
  • After resolving a blocker
  • After user requests fresh start

Context Monitoring

Signs of Context Bloat

Watch for:

  • Repeated information in responses
  • Slower response times
  • Forgetting earlier context
  • Inconsistent references

Context Health Check

Periodically verify:

  • Can still reference key decisions?
  • Can identify current task?
  • Can access state files?
  • Response quality maintained?

State File as External Memory

Use state files as external memory:

What to Store in Files

  • All decisions (ITEM-XXX.md Decisions section)
  • Exploration progress (ITEM-XXX.md Exploration section)
  • Task definitions (ITEM-XXX.md Tasks section)
  • Requirements (ITEM-XXX.md Requirements section)

What to Keep in Context

  • Current phase and task
  • Key constraints
  • Immediate next steps
  • Recent decisions (can reference file for older ones)

Delegation Patterns

Deep Exploration Delegation

Task: Understand how authentication works in this codebase

Instead of:
- Loading all auth-related files into orchestrator context

Do:
- Spawn researcher agent with specific question
- Receive summary findings
- Keep summary in orchestrator context

Implementation Delegation

Task: Implement TASK-005

Instead of:
- Loading full codebase patterns and task into orchestrator

Do:
- Spawn executor with task definition + relevant files only
- Receive completion status
- Update state files

Context Compression Techniques

Summary Generation

After deep work, compress to summary:

Before compression: [Full exploration transcript]

After compression:
**Exploration Result**: Authentication
- Uses JWT tokens
- Stored in localStorage
- Refresh flow in AuthService.refresh()
- Decision needed: token expiry duration

Reference Instead of Inline

BAD: Include full task XML in every message
GOOD: "Executing TASK-005 (see ITEM-XXX.md Tasks section)"

Checkpoint Snapshots

At checkpoints, snapshot key state:

### CHECKPOINT: EXECUTE-001
**Context snapshot**:
- Phase: EXECUTE
- Progress: 5/10 tasks
- Current: TASK-006
- Blocked: None
- Key decisions: Use JWT (DECISION-003)

Integration with Workflow

During DISCUSS

  • Keep exploration map in ITEM-XXX.md
  • Summarize findings per area
  • Reference decisions by ID

During PLAN

  • Read requirements once, create tasks
  • Don't reload requirements repeatedly
  • Reference task IDs not full definitions

During EXECUTE

  • Fresh context per task
  • Load only task + relevant files
  • Update state after each task

During VERIFY

  • Load summary of completed work
  • Cross-reference requirements by ID
  • Keep verification results in ITEM-XXX.md

Best Practices

  1. Reference, don't repeat: Use IDs and file paths
  2. Summarize immediately: After deep work, compress findings
  3. Clean handoffs: Fresh agents get focused context
  4. Use state files: They're your external memory
  5. Monitor bloat: Watch for degradation signs
  6. Delegate proactively: Don't wait until context is full

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

04

需要参考平台分布和安装热度时

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

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

windsurf

29.61%
按下载量换算19

OpenCode

20.19%
按下载量换算13

Codex

16.96%
按下载量换算11

Claude Code

12.7%
按下载量换算8

Antigravity

7.24%
按下载量换算5

Gemini CLI

3.27%
按下载量换算2

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

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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