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Agent Skill · 研究检索

agent-development(Agent 开发)

agent-development 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。

agent-development 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,权限为调用外部服务;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 43,162。

总安装 1,008周安装 42GitHub Stars 33下载 336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:agent-development(Agent 开发)
来源仓库:https://github.com/josiahsiegel/claude-plugin-marketplace
仓库路径:skills/agent-development
安装命令:
npx skills add https://github.com/josiahsiegel/claude-plugin-marketplace --skill agent-development
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/josiahsiegel/claude-plugin-marketplace --skill agent-development

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。

agent-development 用于查找、检索和筛选相关信息,适合快速定位候选结果。适用于需要根据关键词或任务场景从来源线索中获取信息的场景。通过关键词输入和来源仓库筛选来组织和呈现信息。安装前需确认权限范围和维护状态,注意可能触发联网或文件读写操作。

适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/agent-development

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/josiahsiegel/claude-plugin-marketplace --skill…;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

    它需要调用外部服务,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

agent-development 怎么安装?

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

agent-development 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。

agent-development 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

agent-development 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。

agent-development 用的人多吗?

公开数据是累计安装 1,008 次,近一周安装 42 次,下载 336 次,GitHub 33 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。

agent-development 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 第三方扫描已通过,常见的高风险行为没有命中。

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
agent-development

Agent 开发 · 本页

1,00833调用外部服务未明确通过

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

Agent Development for Claude Code Plugins

Overview

Agents are autonomous subprocesses that handle complex, multi-step tasks independently. Each agent is a markdown file in the agents/ directory with YAML frontmatter defining its configuration and a markdown body serving as its system prompt.

Agent File Format

---
name: agent-identifier
description: |
  Use this agent when [triggering conditions].

  <example>
  Context: [Situation]
  user: "[User request]"
  assistant: "[How to respond and invoke agent]"
  <commentary>
  [Why this agent should trigger]
  </commentary>
  </example>

model: inherit
color: blue
tools:
  - Read
  - Write
  - Grep
---

System prompt body in second person ("You are...")

Frontmatter Fields Reference

name (required)

Agent identifier for namespacing and invocation.

RuleDetail
Length3-50 characters
FormatLowercase letters, numbers, hyphens only
Start/endMust be alphanumeric (not hyphen)
ConventionRole-based: code-reviewer, test-generator, domain-expert

Invalid names: ag (too short), -agent- (starts/ends with hyphen), my_agent (underscores)

description (required - most critical field)

Defines WHEN Claude should trigger this agent. Poor descriptions = agent never triggers.

Must include:

  1. Triggering conditions ("Use this agent when...")
  2. 2-4 <example> blocks showing usage scenarios
  3. Each example: context, user request, assistant response, commentary
  4. Both proactive and reactive triggering scenarios

Good description pattern:

description: |
  Use this agent when the user needs help with [domain]. Trigger for:
  - [Scenario 1]
  - [Scenario 2]
  - [Scenario 3]

  <example>
  Context: [Specific situation]
  user: "[What user says]"
  assistant: "[How Claude responds and invokes agent]"
  <commentary>
  [Why this is the right agent for this request]
  </commentary>
  </example>

Common mistake: Vague descriptions without examples. "Helps with code review" will rarely trigger. Include concrete examples with exact user phrases.

Example block rules:

  • Keep example blocks concise — assistant response should be 1-2 sentences, not full code
  • Limit to 3-7 example blocks total (more dilutes matching quality)
  • Do NOT include full JSON schemas, code samples, or CLI output in examples
  • Examples show *when* to trigger and *how to respond*, not the domain content itself

Skill coverage requirement (CRITICAL): When the agent delegates to skills, every skill MUST have at least one <example> block that would route to it. Count skills, count examples, and verify full coverage. If the plugin has 9 skills and only 7 trigger examples, 2 skills will have reduced activation reliability. Add examples until every skill has explicit coverage. When there are more skills than the 7-example limit allows, combine related skills into shared examples that mention both domains.

model (required)

ValueWhen to use
inheritDefault choice - uses parent session's model
sonnetBalanced capability/speed
opusMost capable, for complex reasoning
haikuFast/cheap, for simple validation

Always use inherit unless the agent specifically needs a different capability level.

color (required)

Visual identifier in UI. Choose based on agent function:

ColorUse for
blue / cyanAnalysis, review, research
greenSuccess-oriented, generation, creation
yellowCaution, validation, checking
redCritical, security, destructive operations
magentaCreative, design, architecture

Use distinct colors for different agents within the same plugin.

tools (optional)

Restrict agent to specific tools. Principle of least privilege - only grant what's needed.

# Read-only analysis
tools: ["Read", "Grep", "Glob"]

# Code generation
tools: ["Read", "Write", "Edit", "Grep", "Glob"]

# Full access (omit field entirely)
# tools: (not specified)

Common tool names: Read, Write, Edit, Grep, Glob, Bash, WebSearch, WebFetch, Skill, Agent

MCP tools use format: mcp__server-name__tool-name

System Prompt Design

The markdown body becomes the agent's system prompt. Write in second person ("You are...", "You will...").

Structure Template

You are [role] specializing in [domain].

## Core Responsibilities
1. [Primary responsibility]
2. [Secondary responsibility]

## Process
1. [Step one]
2. [Step two]
3. [Step three]

## Quality Standards
- [Standard 1]
- [Standard 2]

## Output Format
- [What to include]
- [How to structure results]

## Edge Cases
- [Situation]: [How to handle]

Best Practices

DO:

  • Write in second person ("You are...", "You will...")
  • Be specific about responsibilities and process steps
  • Define output format clearly
  • Address edge cases
  • Include skill activation instructions if the agent should load skills
  • Keep the agent body as a lean orchestrator (see below)

DON'T:

  • Write in first person ("I am...", "I will...")
  • Be vague or generic ("help with stuff")
  • Skip process steps
  • Leave output format undefined
  • Omit quality standards
  • Embed domain knowledge that belongs in skills (see below)

Lean Orchestrator Pattern (CRITICAL)

An agent body must be a lean orchestrator, NOT a domain knowledge dump. The agent delegates to skills for detailed knowledge.

Agent Body Size Limits

MetricTargetHard Maximum
Word count1,500-2,500 words3,000 words
Character count~10,000-15,000 chars20,000 chars

What Belongs in the Agent Body

SectionRequiredPurpose
Role identityYes"You are [role] specializing in [domain]"
Skill activation rulesYesTopic-to-skill mapping table
High-level processYesDesign/workflow steps
Output formatYesWhat to include in responses
Brief service summariesOptional2-3 sentences per area to help decide which skill to load
Edge cases / troubleshooting tipsOptionalQuick reference only

What Does NOT Belong in the Agent Body

  • Detailed domain knowledge — belongs in skills
  • Complete CLI/API references — belongs in skill references/
  • Full code examples — belongs in skill examples/
  • Duplicated skill content — if it's in a skill, do NOT repeat it in the agent

Anti-Pattern: Content Duplication

NEVER duplicate content between the agent body and skills. This is the most common mistake and causes massive context bloat.

Bad: Agent body contains a full "Plugin.json Schema" section AND the plugin-master skill also contains it. Good: Agent body says "For plugin.json schema details, load plugin-master:plugin-master" and keeps only a 1-sentence summary.

Lean Orchestrator Template

You are [role] specializing in [domain].

## Skill Activation - CRITICAL
[Topic-to-skill mapping table — this is the heart of the agent]

## Core Responsibilities
[2-5 bullet points on what this agent does]

## Process
[5-7 step workflow for handling user requests]

## Quality Standards
[Brief checklist — 5-10 items]

## Output Format
[What to include in responses]

Description Size Limits

Agent descriptions should be concise and effective:

ElementGuideline
Intro text1-2 sentences on when to trigger
Example blocks3-7 blocks covering diverse scenarios
Total descriptionShould fit naturally — focus on quality trigger examples over length

Agent Design Principles (2025)

Agent-First Plugin Design

  • Primary plugin interface is ONE expert agent named {domain}-expert
  • Plugin named docker-master → agent named docker-expert
  • Only 0-2 slash commands for automation workflows
  • Users interact conversationally, not through command menus

Single Responsibility

Each agent should have a clear, focused purpose. Don't create "do everything" agents. If a plugin needs multiple capabilities, use one expert agent that loads different skills based on context.

Skill Integration

Expert agents should load relevant skills before answering. Include skill activation instructions in the system prompt:

## Skill Activation
When the user asks about [topic], load `plugin-name:skill-name` before responding.

Preventing Trigger Phrase Overlap Between Skills

When a plugin has multiple skills, their trigger phrases and description terms must not create ambiguity. If two skills both claim the same keyword (e.g., both "programmatic-development" and "tmdl-mastery" claim "TMDL"), the agent cannot reliably route requests.

Disambiguation rules:

  1. Audit trigger terms across all skills — list every trigger phrase from every skill description side by side. Flag any term that appears in more than one skill.
  2. Assign exclusive ownership — each ambiguous term must belong to exactly one skill. The other skill should use a more specific phrase (e.g., "TMDL file editing" vs. "programmatic deployment using TMDL").
  3. Add disambiguation hints to the agent's skill activation table — for terms that could route to multiple skills, add a clarifying note: "TMDL editing/syntax → tmdl-mastery; TMDL in deployment pipelines → programmatic-development".
  4. Test with ambiguous queries — after writing descriptions, mentally test phrases like "help me with TMDL" and verify the routing is unambiguous.

Validation Checklist

Before finalizing an agent:

  • Name: 3-50 chars, lowercase, hyphens, starts/ends alphanumeric
  • Description: includes triggering conditions and 2-4 <example> blocks
  • Every skill has trigger coverage: count skills and verify each has at least one example that routes to it
  • No trigger phrase overlap: no ambiguous keyword claimed by multiple skills without disambiguation
  • Model: set to inherit (unless specific need)
  • Color: appropriate for agent function
  • Tools: restricted to minimum needed (or omitted for full access)
  • System prompt: second person, clear responsibilities, defined process and output
  • Frontmatter: valid YAML with all required fields
  • File location: agents/agent-name.md

Testing

  1. Write agent with specific triggering examples
  2. Use similar phrasing to examples in your test queries
  3. Verify Claude loads the agent for matching requests
  4. Test that the agent follows its defined process
  5. Check output matches defined format
  6. Test edge cases mentioned in system prompt

Common Mistakes

MistakeFix
Vague description without examplesAdd 2-4 <example> blocks with concrete user phrases
Skills without trigger examplesEvery skill must have at least one example that routes to it — count and verify
Trigger phrase overlap between skillsAudit all skill descriptions for shared keywords; assign exclusive ownership or add disambiguation
model: sonnet when inherit worksUse inherit unless agent needs specific capability
Too many tools grantedRestrict to minimum needed tools
Generic system promptBe specific about process, output format, quality standards
No skill activationAdd skill loading instructions for knowledge-dependent agents
Multiple agents in one pluginUse one expert agent with skills for different topics
Example blocks with full code/JSONKeep examples concise (1-2 sentence responses); code belongs in skills
Same cross-cutting block in every skillPut platform guidelines in agent body or one shared reference, not each SKILL.md

平台分布

Codex

37.57%
按下载量换算126

Claude

29.62%
按下载量换算100

Cursor

19.47%
按下载量换算65

Gemini CLI

9.41%
按下载量换算32

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。目前只有一个公开来源,建议同时核对源仓库。

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