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claude-artifact-creator

@thapaliyabikendra/ai-artifacts
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Creates, improves, and validates Claude Code artifacts (skills, agents, commands, hooks). Use when creating domain expertise skills, specialized task agents, user-invoked commands, extending Claude Code capabilities, improving existing artifacts, reviewing artifact quality, analyzing code for automation opportunities, or consolidating duplicate artifacts.

Install Skill

1Download skill
2Enable skills in Claude

Open claude.ai/settings/capabilities and find the "Skills" section

3Upload to Claude

Click "Upload skill" and select the downloaded ZIP file

Note: Please verify skill by going through its instructions before using it.

SKILL.md

name claude-artifact-creator
description Creates, improves, and validates Claude Code artifacts (skills, agents, commands, hooks). Use when creating domain expertise skills, specialized task agents, user-invoked commands, extending Claude Code capabilities, improving existing artifacts, reviewing artifact quality, analyzing code for automation opportunities, or consolidating duplicate artifacts.
layer 4
tech_stack agnostic, markdown, yaml
topics skills, agents, commands, hooks, claude-code, artifacts, meta
depends_on
complements
keywords Skill, Agent, Command, Hook, SKILL.md, frontmatter, YAML, prompt-engineering

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

```{lang}
// 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:

```yaml
---
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

Field Requirements
name Max 64 chars, lowercase, hyphens only, no reserved words (anthropic, claude)
description Max 1024 chars, third-person voice, 3+ trigger scenarios, no XML tags
tools Comma-separated; omitting grants ALL tools (including MCP)
model haiku (fast), sonnet (balanced), opus (powerful)
permissionMode default, 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

Type Command
Skill python scripts/init_skill.py <name> --template <type>
Agent python scripts/init_agent.py <name> --template <type> --category <cat>
Command python 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):

Agent Purpose Mode
Plan Research before presenting plan Read-only, plan mode
Explore Fast codebase search Read-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

Pitfall Detection Fix
Vague triggers Description <100 chars Add 3+ specific scenarios
Abstract only No code blocks Add before/after examples
Monolithic >500 lines Move to references/
Kitchen sink Lists 5+ domains Create specialized artifacts
Embedded code in agent Code blocks in agent Extract 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:

Technique Purpose
Semantic skill categorization Organize skills by METHODOLOGY, DOMAIN, LENS, OUTPUT
Explicit workflow pipeline Declarative GATHER → ANALYZE → REPORT in frontmatter
Skill invocation guidance Phase-to-skill mapping with fallback checks
Project-agnostic design Dynamic context loading from docs/
Output externalization Dedicated 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

Field Purpose Format
understands Concepts agent knows List of paths relative to knowledge/concepts/
applies Implementations agent uses List 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/ 3 1
engineers/ 2 2
architects/ 3 0
specialists/ 1 0

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:

Metric Target
Trigger accuracy Activates on relevant requests
Output consistency Same quality across similar inputs
Model compatibility Works with Haiku, Sonnet, Opus
Line count Skills <500, Agents <150
Description length 100-1024 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