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claude-artifact-creatorClaude artifact creator 搜索

Agent Skill

claude-artifact-creator 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

294

周安装

12

GitHub Stars

21

下载量

95
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:claude-artifact-creator(Claude artifact creator 搜索)
来源仓库:https://github.com/thapaliyabikendra/ai-artifacts
仓库路径:skills/claude-artifact-creator
安装命令:
npx skills add https://github.com/thapaliyabikendra/ai-artifacts --skill claude-artifact-creator
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/thapaliyabikendra/ai-artifacts --skill claude-artifact-creator

简介

claude-artifact-creator 用于创建和改进 Claude Code 扩展组件,遵循官方最佳实践。

  • 适合开发新技能包或构建具有专门任务的代理时参考使用。
  • 创建前必读 .claude/GUIDELINES.md 中的决策框架和质量清单,明确技能与代理的区别。
  • 需确认仓库活跃度及是否涉及敏感系统目录的写入权限。
  • 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

Claude Artifact Creator

Creates, improves, and maintains Claude Code extensions following official best practices.

FIRST: Read Meta-Knowledge

Before creating any artifact, READ .claude/GUIDELINES.md for:

  • Decision framework (Skill vs Agent vs Command vs Hook)
  • Tool permissions strategy by role
  • Hook events and configuration
  • Agent/Skill/Command file formats
  • Quality checklists and anti-patterns

This skill provides quick patterns; GUIDELINES.md provides authoritative rules.

When to Use This Skill

  • Creating a new skill for domain expertise or file processing
  • Creating an agent for specialized tasks with context isolation
  • Creating a command for user-invoked shortcuts
  • Improving or refactoring existing artifacts
  • Reviewing artifacts against quality standards
  • Analyzing staged changes for automation opportunities
  • Consolidating duplicate or overlapping artifacts

Core Principle: Concise is Key

The context window is a shared resource. Before adding content, ask:

  • "Does Claude really need this?" - Claude is already smart
  • "Can this be in a reference file?" - Progressive disclosure
  • "Does this justify its token cost?" - Every line has a cost

Core Capabilities

  1. Create - Generate artifacts from templates with proper structure
  2. Improve - Enhance based on official best practices and patterns
  3. Review - Audit against quality checklist and anti-patterns
  4. Consolidate - Merge duplicate artifacts into focused ones

Three-Layer Knowledge Architecture

CRITICAL: Before creating any knowledge artifact, determine the correct layer.

See GUIDELINES.md § Three-Layer Knowledge Architecture for full details.

Quick Decision Flow

Is it a design principle that applies to ANY language?
│
├── YES → Create CONCEPT (knowledge/concepts/)
│         NO CODE, just principles
│
└── NO → Is it specific to a language/framework?
         │
         ├── YES → Create IMPLEMENTATION (knowledge/implementations/{lang}/)
         │         CODE EXAMPLES, links to concept
         │
         └── NO → Create SKILL (skills/)
                  ORCHESTRATION, references both

Creating Concepts

Location: knowledge/concepts/{topic}/{concept}.md

Rules:

  • ✅ Framework-independent principles only
  • ✅ Why it matters (rationale)
  • ✅ How to detect violations (criteria, not code)
  • ❌ NO code examples
  • ❌ NO language-specific syntax

Template:

---
name: {Concept Name}
category: {topic}
implementations:
  dotnet: ../implementations/dotnet/{file}.md#{anchor}
  react: ../implementations/react/{file}.md#{anchor}
used_by_skills: []
---

# {Concept Name}

> "{Quote or one-liner definition}"

## The Principle

{Framework-independent explanation}

## Why It Matters

{Business/technical rationale}

## How to Detect Violations

- {Detection criteria - NO code}
- {Observable symptoms}

## Related Concepts

- [{Related Concept}](../{related}/concept.md)

## Implementations

| Language | Guide |
|----------|-------|
| C#/.NET | [Link](../../implementations/dotnet/{file}.md) |
| React | [Link](../../implementations/react/{file}.md) |

Creating Implementations

Location: knowledge/implementations/{lang}/{file}.md

Rules:

  • ✅ Links to concept(s) it implements
  • ✅ ❌ Bad / ✅ Good code examples
  • ✅ Framework-specific notes
  • ❌ NO principle definitions (link instead)
  • ❌ NO "why" explanations (concept layer)

Template:

---
implements_concepts:
  - concepts/{topic}/{concept}
language: {csharp|typescript|python}
framework: [{dotnet|react|abp}]
---

# {Concept Name} in {Language}

## {Concept} {#anchor}

> **Concept**: [{Concept Name}](../../concepts/{topic}/{concept}.md)

### ❌ Violation

// Code showing anti-pattern


### ✅ Correct

// Code showing correct implementation


## Framework-Specific Notes

{Any framework-specific considerations}

Updating Skills for Three-Layer

When creating or updating skills, add these front matter fields:

---
name: skill-name
applies_concepts:
  - knowledge/concepts/{topic}/{concept}
uses_implementations:
  - knowledge/implementations/{lang}/{file}
---

Governance Checklist

Before creating ANY knowledge artifact:

  • Concept exists? If creating implementation, verify concept exists first
  • No code in concept? Concepts must be code-free
  • Links bidirectional? Concept → Implementation, Implementation → Concept
  • INDEX updated? Add to knowledge/concepts/INDEX.md or knowledge/implementations/INDEX.md

Quick Start

Create a skill:

python scripts/init_skill.py pdf-processor --path .claude/skills --template tool

Create an agent:

python scripts/init_agent.py abp-code-reviewer --path .claude/agents --template reviewer --category reviewers

Create a command:

python scripts/init_command.py run-tests --path .claude/commands --template workflow --category tdd

Key Patterns

1. Decision Pattern

User triggers explicitly → COMMAND
Claude auto-detects → SKILL (no isolation) or AGENT (with isolation)
Deterministic on events → HOOK

2. Progressive Disclosure

Level 1: description (~100 tokens) → Trigger matching
Level 2: SKILL.md body (<5k tokens) → When activated
Level 3: references/ → On-demand deep dives

3. Artifact Limits

See GUIDELINES.md § Size Limits for authoritative limits.

Quick reference: Skills <500, Agents <150, References one level deep.

4. Description Pattern

# Good: Third-person with triggers
description: Processes PDF files for text extraction and form filling.
  Use when working with PDFs, extracting text, or filling forms.

# Bad: First-person or vague
description: I can help you with documents

YAML Validation Rules

FieldRequirements
nameMax 64 chars, lowercase, hyphens only, no reserved words (anthropic, claude)
descriptionMax 1024 chars, third-person voice, 3+ trigger scenarios, no XML tags
toolsComma-separated; omitting grants ALL tools (including MCP)
modelhaiku (fast), sonnet (balanced), opus (powerful)
permissionModedefault, acceptEdits, bypassPermissions

Decision Flowchart

See GUIDELINES.md § Choosing the Right Tool for the full decision matrix.

Quick reference: Command (user triggers) → Skill (auto, no isolation) → Agent (auto, isolated) → Hook (deterministic events)

Creation Workflow

Step 1: Identify Type

Type Decision Checklist:
- [ ] User invokes with /command? → Command
- [ ] Needs separate context window? → Agent
- [ ] Auto-triggered domain knowledge? → Skill
- [ ] Shell action on tool events? → Hook

Step 2: Gather Requirements

Skills: Trigger scenarios (3+), resources needed, primary workflow Agents: Team role, tools needed (least privilege), permission mode Commands: Arguments, phases, expected output

Step 3: Initialize

TypeCommand
Skillpython scripts/init_skill.py <name> --template <type>
Agentpython scripts/init_agent.py <name> --template <type> --category <cat>
Commandpython scripts/init_command.py <name> --template <type> --category <cat>

Templates:

  • Skills: default, tool, workflow, domain, analysis, integration, generator, pattern
  • Agents: architect, reviewer, developer, coordinator, specialist
  • Commands: review, generate, debug, workflow, git, refactor

Step 4: Test

Testing Checklist:
- [ ] Customize all placeholders ([DOMAIN], [TARGET])
- [ ] Test with Haiku - enough guidance?
- [ ] Test with Sonnet - clear and efficient?
- [ ] Test with Opus - not over-explained?
- [ ] Verify triggers activate correctly

Built-in Subagents

Claude Code includes built-in agents (cannot be modified):

AgentPurposeMode
PlanResearch before presenting planRead-only, plan mode
ExploreFast codebase searchRead-only (ls, find, cat, head, tail)

Note: Subagents cannot spawn other subagents.

Tool Permissions & Hook Events

⚠️ Warning: Omitting tools grants ALL tools including MCP. Always whitelist explicitly.

Full reference: See GUIDELINES.md § Agents for tool permissions by role, and GUIDELINES.md § Hooks for hook events.

Best Practices

  1. Concise over comprehensive - Claude is smart; add only what it doesn't know
  2. Show, don't tell - Examples beat descriptions
  3. Third-person descriptions - Required for system prompt injection
  4. 3+ trigger scenarios - Specific scenarios in description ensure activation
  5. Least privilege tools - Only grant necessary tools
  6. One level deep references - No nested references (causes partial reads)
  7. Test all models - What works for Opus may need more detail for Haiku
  8. Validate before shipping - Run scripts/validate.py --strict

Common Pitfalls

PitfallDetectionFix
Vague triggersDescription <100 charsAdd 3+ specific scenarios
Abstract onlyNo code blocksAdd before/after examples
Monolithic>500 linesMove to references/
Kitchen sinkLists 5+ domainsCreate specialized artifacts
Embedded code in agentCode blocks in agentExtract to skill
First-person description"I can help"Use third-person

See references/anti-patterns.md for comprehensive list.

Agent Refactoring

When agents grow >150 lines, extract embedded content to skills, commands, or docs.

Full guide: See agent-refactoring-guide.md

Agent Optimization Patterns

For comprehensive agent optimization, see agent-optimization-patterns.md.

Key techniques:

TechniquePurpose
Semantic skill categorizationOrganize skills by METHODOLOGY, DOMAIN, LENS, OUTPUT
Explicit workflow pipelineDeclarative GATHER → ANALYZE → REPORT in frontmatter
Skill invocation guidancePhase-to-skill mapping with fallback checks
Project-agnostic designDynamic context loading from docs/
Output externalizationDedicated format skill for report templates

Quick optimization checklist:

- [ ] Skills categorized semantically (not alphabetically)
- [ ] Workflow defined as pipeline with phase-to-skill mapping
- [ ] Fallback checks provided for skill failures
- [ ] No hardcoded project names/paths
- [ ] Output template in dedicated skill
- [ ] Quality self-check categorized by concern
- [ ] Agent size <150 lines

Agent Knowledge Profiles

Agents declare their knowledge profile in YAML front matter to enable validation and discoverability.

See GUIDELINES.md § Artifact Knowledge Rules for full governance.

Required Front Matter Fields

FieldPurposeFormat
understandsConcepts agent knowsList of paths relative to knowledge/concepts/
appliesImplementations agent usesList of paths relative to knowledge/implementations/

Example

---
name: abp-developer
understands:
  - solid/srp
  - solid/dip
  - clean-code/naming
  - clean-architecture/layers
applies:
  - dotnet/solid
  - dotnet/clean-code
---

Validation Rules

  1. Path validation: All understands paths must exist in knowledge/concepts/INDEX.md
  2. Path validation: All applies paths must exist in knowledge/implementations/INDEX.md
  3. Wildcard support: Use solid/* to include all concepts in a category
  4. Role requirements: Agents must meet minimum counts for their category

Role Requirements

Role (folder)understands (min)applies (min)
reviewers/31
engineers/22
architects/30
specialists/10

Validation Checklist

When creating or updating agents:

  • All understands paths exist in concepts INDEX
  • All applies paths exist in implementations INDEX
  • Agent meets minimum requirements for its role category
  • Skills align with knowledge profile (related domains)

Cross-reference: See ARTIFACT-KNOWLEDGE-MATRIX.md for full coverage.

Success Metrics

Track these for artifact quality:

MetricTarget
Trigger accuracyActivates on relevant requests
Output consistencySame quality across similar inputs
Model compatibilityWorks with Haiku, Sonnet, Opus
Line countSkills <500, Agents <150
Description length100-1024 chars with triggers

Quality Checklist

See GUIDELINES.md § Quality Checklists for authoritative checklists.

Quick validation:

  • Description: third-person, 100-1024 chars, 3+ triggers
  • Name: lowercase, hyphens, max 64 chars
  • Under line limits (per GUIDELINES.md)
  • Tested with Haiku, Sonnet, and Opus

Integration Patterns

Command → Agent → Skill

/add-feature (command)
  └─ Uses backend-architect (agent)
       └─ Applies api-design-principles (skill)

Skill as Knowledge, Command as Action

Rule: "Knowing" = Skill, "Doing" = Command
      "Doing with Knowledge" = Command referencing Skills

References

Primary (READ FIRST):

Skill-Specific:

Project Context:

  • CLAUDE.md - Project-specific values and quick references

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

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

35.64%
按下载量换算34

Claude

31.44%
按下载量换算30

Cursor

16.36%
按下载量换算16

Gemini CLI

8.19%
按下载量换算8

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/thapaliyabikendra/ai-artifacts --skill claude-artifact-creator 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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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