Customization

Before executing, check for user customizations at: ~/.claude/skills/CORE/USER/SKILLCUSTOMIZATIONS/Prompting/

If this directory exists, load and apply any PREFERENCES.md, configurations, or resources found there. These override default behavior. If the directory does not exist, proceed with skill defaults.

Prompting - Meta-Prompting & Template System

Invoke when: meta-prompting, template generation, prompt optimization, programmatic prompt composition, creating dynamic agents, generating structured prompts from data.

Overview

The Prompting skill owns ALL prompt engineering concerns:

• Standards - Anthropic best practices, Claude 4.x patterns, empirical research

• Templates - Handlebars-based system for programmatic prompt generation

• Tools - Template rendering, validation, and composition utilities

• Patterns - Reusable prompt primitives and structures

This is the "standard library" for prompt engineering - other skills reference these resources when they need to generate or optimize prompts.

Core Components

1. Standards.md

Complete prompt engineering documentation based on:

• Anthropic's Claude 4.x Best Practices (November 2025)

• Context engineering principles

• The Fabric prompt pattern system

• 1,500+ academic papers on prompt optimization

Key Topics:

• Markdown-first design (NO XML tags)

Voice Notification

When executing a workflow, do BOTH:

Send voice notification:

curl -s -X POST http://localhost:8888/notify
-H "Content-Type: application/json"
-d '{"message": "Running the WORKFLOWNAME workflow from the Prompting skill"}' \

/dev/null 2>&1 &

Output text notification:

Running the WorkflowName workflow from the Prompting skill...

Full documentation: ~/.claude/skills/CORE/SkillNotifications.md

• Claude 4.x behavioral characteristics

• Multi-context window workflows

• Agentic coding best practices

• Output format control

• The Ultimate Prompt Template

2. Templates/ - Five Core Primitives

The templating system enables prompts that write prompts - dynamic composition where structure is fixed but content is parameterized.

Directory Structure:

Templates/ ├── Primitives/ # Five core template patterns │ ├── Roster.hbs # Agent/skill definitions from data │ ├── Voice.hbs # Personality calibration settings │ ├── Structure.hbs # Multi-step workflow patterns │ ├── Briefing.hbs # Agent context handoff │ └── Gate.hbs # Validation checklists ├── Examples/ # Sample data and usage └── (Evals/) # Eval-specific templates (from Evals skill)

The Five Primitives:

Primitive Purpose Use Case

ROSTER Data-driven definitions 32 RedTeam agents, 83 skills, voice configs

VOICE Personality calibration Voice parameters, rate, archetype mapping

STRUCTURE Workflow patterns Phased analysis, round-based debate, pipelines

BRIEFING Agent context handoff Research queries, delegation, task assignment

GATE Validation checklists Quality gates, completion checks, verification

3. Tools/

RenderTemplate.ts - Core rendering engine

bun run ~/.claude/skills/Prompting/Tools/RenderTemplate.ts
--template Primitives/Briefing.hbs
--data path/to/data.yaml
--output path/to/output.md

ValidateTemplate.ts - Template syntax checker

bun run ~/.claude/skills/Prompting/Tools/ValidateTemplate.ts
--template Primitives/Briefing.hbs
--data path/to/sample-data.yaml

4. Template Syntax

The system uses Handlebars notation (Anthropic's official syntax):

Syntax Purpose Example

{{variable}}

Simple interpolation Hello {{name}}

{{object.property}}

Nested access {{agent.voice_id}}

{{#each items}}...{{/each}}

Iteration List generation

{{#if condition}}...{{/if}}

Conditional Optional sections

{{> partial}}

Include partial Reusable components

Usage Examples

Example 1: Using Briefing Template (Agent Skill)

// skills/Agents/Tools/AgentFactory.ts import { renderTemplate } from '~/.claude/skills/Prompting/Tools/RenderTemplate.ts';

const prompt = renderTemplate('Primitives/Briefing.hbs', { briefing: { type: 'research' }, agent: { id: 'EN-1', name: 'Skeptical Thinker', personality: {...} }, task: { description: 'Analyze security architecture', questions: [...] }, output_format: { type: 'markdown' } });

Example 2: Using Structure Template (Workflow)

Data: phased-analysis.yaml

phases:

• name: Discovery purpose: Identify attack surface steps:
  • action: Map entry points instructions: List all external interfaces...
• name: Analysis purpose: Assess vulnerabilities steps:
  • action: Test boundaries instructions: Probe each entry point...

bun run RenderTemplate.ts
--template Primitives/Structure.hbs
--data phased-analysis.yaml

Example 3: Custom Agent with Voice Mapping

// Generate specialized agent with appropriate voice const agent = composeAgent(['security', 'skeptical', 'thorough'], task, traits); // Returns: { name, traits, voice: 'default', voiceId: 'VOICE_ID...' }

Integration with Other Skills

Agents Skill

• Uses Templates/Primitives/Briefing.hbs for agent context handoff

• Uses RenderTemplate.ts to compose dynamic agents

• Maintains agent-specific template: Agents/Templates/DynamicAgent.hbs

Evals Skill

• Uses eval-specific templates: Judge, Rubric, TestCase, Comparison, Report

• Leverages RenderTemplate.ts for eval prompt generation

• Eval templates may be stored in Evals/Templates/ but use Prompting's engine

Development Skill

• References Standards.md for prompt best practices

• Uses Structure.hbs for workflow patterns

• Applies Gate.hbs for validation checklists

Token Efficiency

The templating system eliminated ~35,000 tokens (65% reduction) across PAI:

Area Before After Savings

SKILL.md Frontmatter 20,750 8,300 60%

Agent Briefings 6,400 1,900 70%

Voice Notifications 6,225 725 88%

Workflow Steps 7,500 3,000 60%

TOTAL ~53,000 ~18,000 65%

Best Practices

1. Separation of Concerns

• Templates: Structure and formatting only

• Data: Content and parameters (YAML/JSON)

• Logic: Rendering and validation (TypeScript)

2. Keep Templates Simple

• Avoid complex logic in templates

• Use Handlebars helpers for transformations

• Business logic belongs in TypeScript, not templates

3. DRY Principle

• Extract repeated patterns into partials

• Use presets for common configurations

• Single source of truth for definitions

4. Version Control

• Templates and data in separate files

• Track changes independently

• Enable A/B testing of structures

References

Primary Documentation:

• Standards.md

• Complete prompt engineering guide

• Templates/README.md

• Template system overview (if preserved)

• Tools/RenderTemplate.ts

• Implementation details

Research Foundation:

• Anthropic: "Claude 4.x Best Practices" (November 2025)

• Anthropic: "Effective Context Engineering for AI Agents"

• Anthropic: "Prompt Templates and Variables"

• The Fabric System (January 2024)

• "The Prompt Report" - arXiv:2406.06608

• "The Prompt Canvas" - arXiv:2412.05127

Related Skills:

• Agents - Dynamic agent composition

• Evals - LLM-as-Judge prompting

• Development - Spec-driven development patterns

Philosophy: Prompts that write prompts. Structure is code, content is data. Meta-prompting enables dynamic composition where the same template with different data generates specialized agents, workflows, and evaluation frameworks. This is core PAI DNA - programmatic prompt generation at scale.