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Agent Skill · 研究检索

claude-prompting(Claude prompting 搜索)

用于辅助提示词、系统指令、Agent 行为约束和工作流模板的整理。它适合让 Agent 规范任务边界、统一输出格式、拆分操作步骤或优化提示词可复用性。使用时需要保留真实业务约束,不要把示例当硬规则;涉及自动执行、外部工具或高风险操作时,应在提示词中明确确认步骤、权限边界和失败处理方式。

claude-prompting 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 58,406。

总安装 416周安装 17GitHub Stars 4下载 133核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:claude-prompting(Claude prompting 搜索)
来源仓库:https://github.com/duyet/claude-plugins
仓库路径:skills/claude-prompting
安装命令:
npx skills add https://github.com/duyet/claude-plugins --skill claude-prompting
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/duyet/claude-plugins --skill claude-prompting

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于优化针对 Claude 模型的提示词设计和系统指令构建。支持长上下文处理、结构化标签和扩展推理模式。通过 npx 安装后可用于提示词模板化和工作流标准化。建议保留真实业务约束,避免将示例提示词当作硬性规则。claude-prompting 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/claude-prompting

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/duyet/claude-plugins --skill claude-prompting;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

claude-prompting 怎么安装?

在终端执行 npx skills add https://github.com/duyet/claude-plugins --skill claude-prompting。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

claude-prompting 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

claude-prompting 需要什么权限?

权限级别是需要联网。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。

claude-prompting 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

claude-prompting 用的人多吗?

公开数据是累计安装 416 次,近一周安装 17 次,下载 133 次,GitHub 4 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

claude-prompting 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
claude-prompting

Claude prompting 搜索 · 本页

4164需要联网未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Claude Prompt Engineering

Claude is Anthropic's AI assistant designed to be helpful, harmless, and honest. It excels at long-context tasks, follows complex instructions precisely, and works best with well-structured prompts using XML-style tags.

When to Invoke This Skill

Use this skill when:

  • Crafting prompts specifically for Claude/Anthropic models (default: Claude Sonnet 4.5)
  • Working with long documents or large context (up to 1M tokens with Sonnet 4.5 beta)
  • Using structured prompts with XML-style tags
  • Implementing extended thinking for complex reasoning
  • Requiring precise instruction following
  • Building agentic workflows with parallel tool use

Claude's Identity & Characteristics

AttributeDescription
PersonalityHelpful, harmless, honest
Constitutional AIBuilt-in safety and ethical guidelines
Context WindowUp to 1M tokens (Sonnet 4.5 beta), 200K standard
StrengthsLong-context analysis, instruction following, document understanding, agentic tasks
Prompt StyleStructured, clear, XML-style formatting
Extended ThinkingOptional reasoning trace feature with tool use

Universal Prompting Techniques (Claude-Adapted)

1. Zero-Shot Prompting

Claude responds well to clear, direct zero-shot prompts.

Good Example:

Extract the key dates and events from the following text:

<text>
[paste text]
</text>

Output format: JSON with keys "date", "event", "description"

Less Effective:

Can you tell me what dates are in this text?

2. Few-Shot Prompting (Multishot)

Use well-formatted examples with XML structure.

<examples>
<example>
<input>
The conference is scheduled for March 15, 2025 in San Francisco.
</input>
<output>
{
  "date": "2025-03-15",
  "event": "conference",
  "location": "San Francisco"
}
</output>
</example>

<example>
<input>
Our next board meeting is on June 22nd.
</input>
<output>
{
  "date": "2025-06-22",
  "event": "board meeting"
}
</output>
</examples>

<input>
The product launches on September 1st in New York.
</input>

<output>

3. Chain-of-Thought Prompting

Claude has an Extended Thinking feature that shows reasoning (enabled via API, output in response):

I need to decide between these two job offers. Let me think through this step by step.

<job_offer_a>
[details]
</job_offer_a>

<job_offer_b>
[details]
</job_offer_b>

Please analyze both offers, show your reasoning, and provide a recommendation.

API enables extended thinking; response includes:

<thinking>
First, let me analyze the compensation...
Then consider the growth potential...
The work-life balance factors are...
The company stability differs by...
</thinking>

<answer>
[conclusion]
</answer>

4. Zero-Shot CoT

Simply add "Let's think step by step" or similar:

What's the most efficient route to visit all these cities?

Let's think step by step.

5. Prompt Chaining with XML Tags

Break complex tasks using XML delimiters:

Chain Step 1:

<task>
Extract relevant quotes from this document related to [topic].
</task>

<document>
[paste document]
</document>

<output_format>
<quotes>
<quote>[relevant quote 1]</quote>
<quote>[relevant quote 2]</quote>
</quotes>
</output_format>

Chain Step 2:

<task>
Summarize the extracted quotes and synthesize key insights.
</task>

<quotes>
[from previous response]
</quotes>

<output_format>
<summary>
[executive summary]
</summary>

<key_insights>
<insight>[insight 1]</insight>
<insight>[insight 2]</insight>
</key_insights>
</output_format>

6. ReAct Prompting

Use structured thought-action-observation cycles:

<question>
[research question]
</question>

<thought_1>
[what needs to be done first]
</thought_1>

<action_1>
[tool use or information gathering]
</action_1>

<observation_1>
[result from action]
</observation_1>

<thought_2>
[next step based on observation]
</thought_2>

<final_answer>
[conclusion]
</final_answer>

7. Tree of Thoughts

Use multiple reasoning paths with XML structure:

<problem>
[complex problem]
</problem>

<thought_paths>
<path_1>
<assumption>[approach 1]</assumption>
<reasoning>[step-by-step]</reasoning>
<conclusion>[result]</conclusion>
</path_1>

<path_2>
<assumption>[approach 2]</assumption>
<reasoning>[step-by-step]</reasoning>
<conclusion>[result]</conclusion>
</path_2>

<path_3>
<assumption>[approach 3]</assumption>
<reasoning>[step-by-step]</reasoning>
<conclusion>[result]</conclusion>
</path_3>
</thought_paths>

<synthesis>
[best path and why]
</synthesis>

Claude-Specific Best Practices

1. Use XML-Style Tags for Structure

Claude's official courses extensively use XML tags:

<context>
[background information]
</context>

<task>
[what needs to be done]
</task>

<examples>
[example inputs and outputs]
</examples>

<input>
[the actual input to process]
</input>

<output_format>
[expected format]
</output_format>

2. Structure Long Prompts Hierarchically

From Anthropic's official courses:

[TASK_CONTEXT]
Setting the stage and overall context

[TONE_CONTEXT]
How Claude should approach the task

[INPUT_DATA]
The actual data to work with

[EXAMPLES]
Few-shot examples

[TASK_DESCRIPTION]
Specific task details

[IMMEDIATE_TASK]
The immediate action to take

[OUTPUT_FORMATTING]
Expected output structure

3. Leverage Extended Thinking

For complex reasoning, enable Claude's extended thinking via the API:

API Syntax (Python SDK):

response = client.messages.create(
    model="claude-sonnet-4-5-20250929",
    max_tokens=4096,
    thinking={
        "type": "enabled",
        "budget_tokens": 8192
    },
    messages=[{
        "role": "user",
        "content": "Analyze this complex problem..."
    }]
)

Prompt-Side (XML structure for expected output):

<task>
[complex reasoning task]
</task>

<thinking>
[Claude will show its reasoning here]
</thinking>

<answer>
[final answer]
</answer>

Key Points:

  • budget_tokens sets max tokens for reasoning (must be < max_tokens)
  • Claude 4.5 returns summarized thinking by default
  • First few lines are more verbose (useful for prompt engineering)
  • You're billed for full thinking tokens, not summary tokens

4. Use System Prompts Effectively

System prompts set Claude's behavior:

System: You are a technical writer specializing in API documentation. Your responses are always:
- Clear and concise
- Technically accurate
- Formatted with Markdown
- Focused on developer needs

User: [your actual query]

5. Prefill Claude's Response

Guide the format by starting Claude's response:

<task>
Analyze this document and extract key findings.
</task>

<document>
[paste document]
</document>

<response>
<summary>
[Claude continues from here]

6. Cache Control for Long Prompts

Optimize for repeated prompts:

<cached_content cache_control="{\"type\":\"ephemeral\"}">
[large context that doesn't change]
</cached_content>

<task>
[specific task that varies]
</task>

7. Claude 4.5 Agent Features

Claude 4.5 introduces powerful agent capabilities:

Parallel Tool Use - Claude can use multiple tools simultaneously:

<task>
Analyze this data and create a visualization.
</task>

<tools>
- Web search for market data
- Code execution for analysis
- File write for chart output
</tools>

Claude will execute these in parallel when possible.

Memory Files - Claude can maintain knowledge across sessions:

<task>
When working on ongoing projects, create a memory file to track:
- Key decisions and rationale
- Project context and constraints
- Preferences and patterns
</task>

Claude will automatically update and reference memory files when given local file access.

Extended Thinking with Tools - Reasoning can pause to use tools:

# API: Enable extended thinking with tool use
response = client.messages.create(
    model="claude-sonnet-4-5-20250929",
    max_tokens=4096,
    thinking={
        "type": "enabled",
        "budget_tokens": 8192
    },
    tools=[web_search_tool],
    messages=[{
        "role": "user",
        "content": "Research [topic] and provide a comprehensive analysis."
    }]
)

# Claude can now use web search DURING extended thinking,
# alternating between reasoning and information gathering.

Anti-Patterns to Avoid

Anti-PatternWhy It FailsBetter Approach
Ambiguous instructionsClaude follows literallyBe explicit about requirements
Missing output formatUnpredictable formattingAlways specify format
No structure in long promptsClaude may lose trackUse XML tags and sections
Ignoring context window limitsTruncation issuesBe mindful of 200K/1M limits
Over-constraining creativityReduces Claude's helpfulnessBalance structure with flexibility

Quick Reference Templates

Document Analysis

<task>
[specific analysis task]
</task>

<document>
[paste document]
</document>

<output_format>
[expected structure]
</output_format>

Code Generation with Examples

<task>
Write a function that [description]
</task>

<requirements>
[specific requirements]
</requirements>

<examples>
<example>
<input>[input example]</input>
<output>[expected output]</output>
</example>
</examples>

<output_format>
[code in specified language]
</output_format>

Data Extraction

<task>
Extract [specific fields] from the following text
</task>

<input_text>
[paste text]
</input_text>

<output_format>
JSON with keys: [list keys]
</output_format>

Extended Thinking

# API: Enable extended thinking
response = client.messages.create(
    model="claude-sonnet-4-5-20250929",
    max_tokens=4096,
    thinking={
        "type": "enabled",
        "budget_tokens": 8192
    },
    messages=[{
        "role": "user",
        "content": """
<task>
[complex reasoning task]
</task>

Please show your reasoning step by step, then provide the final answer.
"""
    }]
)

# Response will include <thinking> block followed by <answer>

Model Capabilities Reference

FeatureClaude Sonnet 4.5Claude Haiku 4.5Claude Opus 4.5Notes
Context Window200K / 1M (beta)200K200KSonnet 4.5: 1M with beta header
Extended Thinking✅ Yes✅ Yes✅ YesWith tool use support
Max Output64K tokens64K tokens64K tokensUnified across 4.5
Vision✅ Yes✅ Yes✅ YesImage analysis
Parallel Tool Use✅ Yes✅ Yes✅ YesClaude 4.5 feature
Memory Files✅ Yes✅ Yes✅ BestLocal file knowledge
Code✅ Excellent✅ Good✅ BestOpus 4.5: SOTA coding
SpeedFastFastestModerateDefault: Sonnet 4.5
Recommendation: Start with Claude Sonnet 4.5 - best balance of intelligence, speed, and cost for most use cases. Use Opus 4.5 for complex coding, Haiku 4.5 for speed-critical tasks.

Migration Notes (Claude 3 → 4.5)

If you're migrating from Claude 3.x to Claude 4.5:

ChangeImpactAction
Default modelSonnet 3.5 → Sonnet 4.5Update model IDs in code
Context window200K → 1M (beta) availableRequires beta header for 1M
Parallel toolsNew capabilityUpdate prompts to leverage parallel execution
Memory filesNew capabilityGrant file access for persistent knowledge
Extended thinking + toolsNew capabilityCan now use tools during reasoning
Max output8K → 64K tokensAdjust output expectations

API Migration:

# Old (Claude 3.5)
model="claude-sonnet-3-5-20240620"

# New (Claude 4.5)
model="claude-sonnet-4-5-20250929"  # or use alias "claude-sonnet-4-5"

Most prompting techniques remain unchanged—XML tags, system prompts, and structured outputs work identically.

Prompt Element Checklist

When creating Claude prompts, consider including:

  • Task Context: Overall purpose and setting
  • Tone Context: How Claude should approach it
  • Input Data: The actual content to process
  • Examples: Few-shot demonstrations (if needed)
  • Task Description: Specific instructions
  • Immediate Task: What to do right now
  • Output Format: Expected structure
  • Prefill: Start of Claude's response (optional)

See Also

  • references/basics.md - Foundational Claude prompting concepts
  • references/techniques.md - Detailed technique explanations
  • references/xml-formatting.md - XML tag patterns and usage
  • references/patterns.md - Reusable Claude prompt patterns
  • references/examples.md - Concrete examples from Anthropic courses
  • grok-prompting skill - For Grok/xAI-specific guidance
  • gemini-prompting skill - For Google Gemini-specific guidance

平台分布

Codex

35.6%
按下载量换算47

Claude

29.53%
按下载量换算39

Cursor

18.68%
按下载量换算25

Gemini CLI

8.52%
按下载量换算11

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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