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agent-creationAgent 创建

Agent Skill

agent-creation 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

220

周安装

9

GitHub Stars

4

下载量

71
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

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:agent-creation(Agent 创建)
来源仓库:https://github.com/joabgonzalez/ai-agents-framework
仓库路径:skills/agent-creation
安装命令:
npx skills add https://github.com/joabgonzalez/ai-agents-framework --skill agent-creation
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/joabgonzalez/ai-agents-framework --skill agent-creation

简介

agent-creation 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。

  • 适用于需要根据关键词或任务场景进行信息检索与筛选的场景。
  • 通过 npx skills add 命令从 GitHub 仓库安装并使用该技能。
  • 安装前建议确认权限范围、维护状态及是否触发联网或文件操作。
  • 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。

SKILL.md

Agent Creation

Create project-specific agent definitions (AGENTS.md) with YAML frontmatter and structured markdown. Agents define purpose, skills, workflows, and policies for AI assistants working on a project.

When to Use

  • Creating a new agent definition from scratch
  • Setting up project-specific agents
  • Documenting agent workflows and responsibilities

Don't use for:

  • Creating individual skills (use skill-creation)
  • Creating context prompts (use prompt-creation)

Critical Patterns

✅ REQUIRED: Select Mode Before Anything Else

Before gathering context or writing any content, determine which mode to use.

Precedence order:

  1. Explicit mode (user specifies) — always respect this

- Keywords: "interview mode", "no context", "ask me questions" - Keywords: "analysis mode", "analyze the project", "read the project"

  1. Auto-detect (if no mode specified):
Is destination project context visible (not the framework itself)?
  YES → Analysis Mode (confirm with user before proceeding)
  NO  → Interview Mode

Auto-detect warning: If the current working directory appears to be the ai-agents-skills framework (e.g., package.json shows "name": "ai-agents-skills"), do not auto-select Analysis Mode. Confirm with the user which project to analyze or switch to Interview Mode.

Signals that destination project context is available:

  • package.json with a project name different from the framework
  • README.md describing the destination project
  • src/ directory with application source code

✅ REQUIRED: Gather Context — Two Modes

Interview Mode (no project context available)

Ask these 9 questions in order. Wait for answers before proceeding.

  1. What is the primary purpose of this agent?
  2. What input will it receive? (files, text, user queries)
  3. What is the expected output format?
  4. Which skills does it need?
  5. Specific workflows, policies, or constraints?
  6. Target audience? (developers, end-users, AI assistants)
  7. Technologies, frameworks, or tools involved?
  8. Project context where this agent operates?
  9. Tone or communication style? (formal, casual, technical)

Do not proceed until all required questions are answered.

Analysis Mode (destination project context is available)

Read files in this order and extract answers to the 9 questions above:

FileExtract
package.jsonProject name, dependencies, framework versions
README.mdProject purpose, architecture overview, tech stack
tsconfig.jsonTypeScript strictness, target, paths
src/ structureMain patterns, component organization, layers
.github/workflows/CI/CD tools, test runners, linting setup
AGENTS.md (existing)Current skills, workflows already defined

After analysis, only ask the user about gaps — information that could not be inferred from the files.

Always confirm your findings before writing: "Based on your project, I found: X, Y, Z. Does this look correct?"


✅ REQUIRED: Frontmatter Structure

name: my-project-agent # Required: lowercase-with-hyphens
description: "Development assistant for Project X. Expert in TypeScript, React, MUI."
license: "Apache 2.0"
metadata:
  version: "1.0"
  skills:
    - typescript
    - react
    - critical-partner # Mandatory for ALL agents
    - code-conventions # Mandatory for coding-related agents
    - a11y
---

Rules:

  • name, description, skills are required
  • Always include critical-partner in skills
  • Use YAML list syntax (- item), never []
  • Omit empty fields completely

✅ REQUIRED: Content Sections

After frontmatter, include:

  1. # Agent Name — Title (e.g., "Alpha Project Agent")
  2. ## Purpose — Clear statement of responsibilities
  3. ## How to Use Skills — Auto-discovery workflow (BEFORE Skills Reference table)
  4. ## Skills Reference — Table: Trigger | Skill | Path (only if skills are already installed)
  5. ## Project Structure & Skills Storage — Symlink explanation (AFTER Skills Reference table)
  6. ## Supported Stack (if applicable) — Technologies and versions
  7. ## Workflows (optional) — Feature dev, code review, bug fix flows
  8. ## Policies (optional) — Typing rules, accessibility, version constraints

✅ REQUIRED: How to Use Skills Section

AGENTS.md must include this section BEFORE the Skills Reference table. It must always include auto-discovery as the primary mechanism.

Key steps (copy full template from references):

  1. Step 1 — Discover: List .{model}/skills/ to find installed skills; read each SKILL.md description
  2. Step 2 — Match: Check Skills Reference table; if absent, scan directory for best match
  3. Step 3 — Read: Open .{model}/skills/{skill-name}/SKILL.md
  4. Step 4 — Dependencies: Read every skill listed in metadata.skills before proceeding
  5. Step 5 — Apply: Follow Critical Patterns (✅ REQUIRED), Decision Tree, and inline examples
Full section template with all sub-steps: agent-templates.md

Why auto-discovery matters: Skills Reference table reflects skills at creation time only; directory listing always reflects current state. Both together ensure 100% coverage.


✅ REQUIRED: Skills Reference Table (Conditional)

Include this section only if skills have been identified — either specified by the user (Interview Mode Q4) or detected from project files (Analysis Mode). If no skills were identified at all, omit this section entirely.

Every identified skill must appear in both places:

  1. metadata.skills in the frontmatter
  2. A row in the Skills Reference table

When included, place it AFTER the How to Use Skills section. Use {model} placeholders for model-agnostic paths.

Full table template: agent-templates.md

✅ REQUIRED: Add "Project Structure & Skills Storage" Section

AGENTS.md must include this section AFTER the Skills Reference table. Explains the 3-layer symlink structure for LLMs that struggle with symlink resolution.

Full section template with symlink diagram: agent-templates.md

❌ NEVER: Skip Mode Selection

Always determine the mode (Interview or Analysis) before gathering any context. Jumping straight to writing the AGENTS.md leads to incomplete or incorrect agent definitions.

❌ NEVER: Analyze the Framework as the Destination Project

If running from within ai-agents-skills, confirm the destination project before using Analysis Mode. Reading the framework's own package.json or README.md produces an agent definition for the wrong project.

❌ NEVER: Include Skills Reference Table When No Skills Are Installed

An empty table or a table with placeholder rows provides no value and misleads the model. Omit the section entirely if no skills exist yet.


Decision Tree

Explicit mode specified by user?
  YES → Use that mode directly
  NO  → Auto-detect:
          Working directory = ai-agents-skills framework?
            YES → Interview Mode (or confirm with user)
            NO  → Destination project files visible?
                    YES → Analysis Mode (confirm findings with user first)
                    NO  → Interview Mode

Interview Mode:
  All 9 questions answered? → NO → Stop: Ask clarifying questions
  → Proceed to create AGENTS.md

Analysis Mode:
  Files read and findings confirmed? → NO → Confirm with user
  All gaps filled? → NO → Ask only about missing information
  → Proceed to create AGENTS.md

Both modes:
  All required skills identified? → NO → Ask: Which skills needed?
  Agent has complex workflows? → YES → Add Workflows section
  Agent has version constraints? → YES → Add Policies section
  Skills installed in project? → YES → Add Skills Reference table
                               → NO  → Omit Skills Reference table
  All referenced skills exist? → NO → Verify paths
  critical-partner in skills? → NO → Must include (mandatory)

Workflow

  1. Select mode → Explicit (user-specified) or auto-detect
  2. Gather context → Analysis Mode: read project files, infer 9 answers, ask only gaps | Interview Mode: ask all 9 questions
  3. Confirm context → Show findings to user before writing (both modes)
  4. Create structuremkdir presets/{project-name} + create AGENTS.md
  5. Write frontmatter → name, description, skills list
  6. Add "How to Use Skills" section → Complete workflow with auto-discovery (BEFORE Skills Reference table)
  7. Write Skills Reference table → Only if skills are installed; use {model} placeholders
  8. Add "Project Structure & Skills Storage" section → Complete symlink documentation (AFTER Skills Reference table)
  9. Write content → Purpose, Supported Stack, Workflows, Policies
  10. Validate → Run checklist below, verify all skills exist

Example

Interview Mode

name: example-agent
description: "Development assistant for Example Project. TypeScript, React, accessibility."
license: "Apache 2.0"
metadata:
  version: "1.0"
  skills:
    - typescript
    - react
    - critical-partner
    - code-conventions
    - a11y

Resulting AGENTS.md structure (abbreviated):

# Example Project Agent

Purpose: Primary development assistant for TypeScript/React best practices and accessibility.

How to Use Skills (MANDATORY WORKFLOW):
  Step 1 — Discover  | Step 2 — Match | Step 3 — Read
  Step 4 — Dependencies | Step 5 — Apply

Skills Reference:
  TypeScript types/interfaces | typescript       | {model}/skills/typescript/SKILL.md
  React components/hooks      | react            | {model}/skills/react/SKILL.md
  Code review                 | critical-partner | {model}/skills/critical-partner/SKILL.md

Project Structure & Skills Storage: 3-layer symlink structure (see template for full diagram)

Supported Stack: TypeScript 5.0+, React 18+, Vite
Policies: Strict typing (no `any`), keyboard-accessible components, React hooks best practices
Full AGENTS.md content with all section templates: agent-templates.md

Edge Cases

Agent with 20+ skills: Group skills in the reference table by category (Framework, Testing, Standards).

Multiple agents per project: Each agent should have distinct responsibility. Avoid skill overlap.

Modifying existing agents: Re-gather context for changed requirements before updating.

No skills installed yet: Omit the Skills Reference table. The auto-discovery section in How to Use Skills is sufficient — the model will find skills as they are installed.

Skills added after creation: The auto-discovery section handles this automatically. No need to update the AGENTS.md when new skills are installed.

When to split one agent into multiple: Split when the agent prompt exceeds ~400 tokens OR the agent covers 2+ unrelated workflows (e.g., frontend development + infrastructure provisioning). Each agent should have one primary job so skill routing stays predictable. Overlap between agents causes the model to load multiple agents unnecessarily.

Updating agent description when project scope changes: The description field in AGENTS.md frontmatter is the routing key — the model uses it to decide which agent to activate. If the project's scope changes (new framework, added backend), re-run the creation workflow to regenerate the description. A stale description causes the wrong agent to be selected or the right one to be skipped.

Skill version conflicts across agents: Skills are installed project-wide, not per-agent. If two agents in the same project reference the same skill, they share the same installed version. After updating a skill with skills sync, both agents get the update simultaneously — verify both agents' behavior after any skill update that changes critical patterns.


Checklist

  • Mode selected (Interview or Analysis) before gathering context
  • In Analysis Mode: confirmed that analyzed context belongs to the destination project, not the framework
  • Context gathered and confirmed with user (both modes)
  • Directory under presets/ (lowercase-with-hyphens)
  • AGENTS.md with frontmatter: name, description, skills
  • critical-partner in skills (mandatory for all)
  • "How to Use Skills" section added BEFORE Skills Reference table, with auto-discovery as Step 1
  • Skills Reference table included ONLY if skills are already installed in the project
  • Skills Reference table uses {model} placeholders (model-agnostic paths)
  • "Project Structure & Skills Storage" section added AFTER Skills Reference table
  • All referenced skills exist in .agents/skills/
  • Purpose section is clear and actionable
  • Token-efficient (no filler words)
  • Follows english-writing skill guidelines

Resources

适合场景

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02

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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

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

Codex

38.29%
按下载量换算27

Claude

27.11%
按下载量换算19

Cursor

18.39%
按下载量换算13

Gemini CLI

8.43%
按下载量换算6

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

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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