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Prompt Template Designer

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Prompt Template Designer

Quick Start

# 1. Check if template-worthy
# Criteria: 2+ uses, 5+ decision points, domain-specific

# 2. Extract pattern
# Identify invariants (constants) vs variants (parameters)

# 3. Create template
# Use Intent → Constraints → Success Criteria structure

Persona

Think like a patterns library designer extracting recurring prompt structures. Identify what varies (parameters) vs what stays constant (pattern), encode domain knowledge into constraints, and design templates that reduce cognitive load while maintaining quality.

Analysis Questions

1. Recurrence Check

"Have I used this pattern 2+ times?"

ScenarioTemplate?
"Generate Git commit message" (daily)YES
"Explain React hooks to new dev" (once)NO
"Debug Bash permission error" (recurring)YES
"Research specific API quirk" (unique)NO

Principle: Premature templating adds maintenance burden. Wait for second use.

2. Variation Analysis

"What stays constant vs what changes?"

TypeWhat It IsExamples
InvariantsTemplate structureIntent verb, core constraints, output format
VariantsParametersFile names, project context, thresholds

3. Complexity Check

"Does this have 5+ decision points?"

High-value template (5+ decisions): Code review prompt (action verb, language, review focus, output format, severity levels, style guide, context, fixes vs identify)

Low-value (1-3 decisions): "Explain specific Git command" → just ask directly

4. Domain Knowledge Check

"Does this encode domain-specific intelligence?"

High-value: Team conventions, quality standards, project constraints Low-value: Generic "ask AI a question" or "generate code"

5. Parameter Design

"What parameters make this flexible but not vague?"

PatternExample
Enum{{ACTION_TYPE}} - Values: [CREATE, DEBUG, REFACTOR]
Path{{TARGET_FILE}} - Type: file_path
Text{{CHANGES_MADE}} - Type: bullet_list
Composite{{ERROR_CONTEXT}} - Required fields: error_message, file_location

Rule: 3-7 parameters optimal. More → split into multiple templates.

Principles

Principle 1: Template When Recurs 2+

  • First use: Write prompt directly
  • Second use: Notice pattern, extract template
  • Third+ uses: Use template, refine

Principle 2: Parameters Over Hard-Coding

# Before (hard-coded)
DEBUG backup.sh with "Permission denied" error

# After (parameterized)
DEBUG {{SCRIPT_NAME}} with "{{ERROR_MESSAGE}}" error

Principle 3: Document Success Patterns

Templates must include:

  • When to use (trigger conditions)
  • Why it works (pattern encoded)
  • Example filled (concrete instantiation)
  • Common mistakes (what to avoid)

Principle 4: Version and Evolve

### v2.0.0 (2025-11-18)
- BREAKING: Changed {{CHANGES}} to structured {{CHANGES_MADE}}
- Added "business value" requirement

### v1.0.0 (2025-10-15)
- Initial extraction from successful prompts

Principle 5: Measure Effectiveness

MetricTarget
Success rate>85%
Time savedMeasurable
Iterations needed<3
Team adoption>50%

Template Structure

---
template_name: {{descriptive-name}}
category: {{create|debug|refactor|optimize|analyze|generate}}
domain: {{backend|frontend|devops|testing|documentation}}
version: {{semantic-version}}
success_rate: {{percentage}}
---

# {{Template Name}}

## When to Use
{{Trigger conditions}}

## Parameters
### {{PARAM_1}}
- **Type**: {{enum|path|text|composite}}
- **Example**: {{value}}
- **Required**: {{yes|no}}

## Template
\```
INTENT:
{{ACTION_VERB}} {{description with parameters}}

CONSTRAINTS:
- {{invariant constraint}}
- {{parameterized constraint using {{PARAM}}}}

SUCCESS CRITERIA:
- {{measurable criterion}}
\```

## Example (Filled)
{{Concrete instantiation}}

## Common Mistakes
- {{Anti-pattern and how to avoid}}

Example: Git Commit Message Generator

---
template_name: git-commit-message-conventional
category: generate
version: 2.0.0
success_rate: 95%
---

## Parameters
- **CHANGES_MADE**: List of changes (required)
- **JIRA_TICKET**: PROJ-NNNN format (required)
- **SCOPE**: [auth, api, ui, db, devops] (required)
- **TYPE**: [feat, fix, docs, refactor, test] (required)

## Template
\```
GENERATE Git commit message

CHANGES: {{CHANGES_MADE}}

CONSTRAINTS:
- Format: {{TYPE}}({{SCOPE}}): <description> [{{JIRA_TICKET}}]
- Subject: Imperative mood, <50 chars
- Body: Explain WHY (business value)

SUCCESS CRITERIA:
- Passes commitlint
- Teammate understands without reading diff
\```

## Example (Filled)
\```
feat(auth): add JWT refresh endpoint [PROJ-1234]

- Add /auth/refresh: improves mobile UX by eliminating re-logins
- Extend token to 24h: reduces authentication friction
\```

## Common Mistakes
- Forgetting Jira ticket
- Past tense ("Added") instead of imperative ("Add")
- Explaining WHAT instead of WHY

Anti-Patterns

Anti-PatternSymptomFix
Template Before PatternCreating for unused promptsUse manually 2+ times first
Over-Parameterization15+ parametersAim for 3-7, split if more
Under-ParameterizationOnly works for one scenarioMust apply to 3+ use cases
No Success MetricsNever tracked qualityTrack success rate, time saved

Quick Reference

Template Creation Checklist:

  • Used pattern 2+ times?
  • Identified constants vs variants?
  • 5+ decision points?
  • Parameters with examples?
  • Filled example included?
  • Success criteria defined?

Parameter Design:

  • Descriptive names (not {{X}})?
  • Type specified?
  • Examples provided?
  • Required/optional marked?

Teaching Integration (L2 → L3)

Transition signal: Student has written similar prompts 2+ times with 85%+ success

Teaching sequence:

  1. "You've done this before. What's similar?" (identify recurrence)
  2. "What constraints appear in both?" (extract constants)
  3. "What changed?" (parameterize variants)
  4. "Let's formalize as reusable intelligence" (create template)

If Verification Fails

  1. Check recurrence: "Has this been used 2+ times?"
  2. Check complexity: "Are there 5+ decision points?"
  3. Check parameters: "3-7 well-designed parameters?"
  4. Stop and report if template adds more cognitive load than it saves

Source

git clone https://github.com/aiskillstore/marketplace/blob/main/skills/92bilal26/prompt-template-designer/SKILL.mdView on GitHub

Overview

Design reusable prompt templates that encode domain-specific patterns for recurring AI tasks. Use when you've executed similar prompts 2+ times to capture the pattern as reusable intelligence and avoid one-off prompts.

How This Skill Works

Assess template-worthiness by checking for 2+ uses, 5+ decision points, and domain specificity. Then extract the pattern by separating invariants from parameters and build a template using the Intent → Constraints → Success Criteria structure. Finally, version and store templates for consistent reuse across projects.

When to Use It

  • You have used a prompt 2+ times and need to capture the pattern as reusable intelligence.
  • You want to codify a domain-specific pattern to reduce cognitive load and training time.
  • Your team needs standardized prompts to ensure consistency across projects.
  • You’re building a versioned templates library and want trackable improvements.
  • Recurring prompts require updates or extensions, and you want to parameterize changes instead of hard-coding.

Quick Start

  1. Step 1: Check if template-worthy (2+ uses, 5+ decision points, domain-specific).
  2. Step 2: Extract pattern by identifying invariants vs variants.
  3. Step 3: Create template using Intent → Constraints → Success Criteria structure.

Best Practices

  • Validate template-worthiness with the 2+ uses and 5+ decision points criterion before templating.
  • Clearly define invariants (structure) vs variants (parameters).
  • Use the Intent → Constraints → Success Criteria structure when crafting templates.
  • Document when to use, why it works, a concrete example, and common mistakes for each template.
  • Version templates and monitor adoption, time saved, and success rates to guide evolution.

Example Use Cases

  • Code review prompt template specifying action verb, language, focus area, output format, and severity.
  • Git commit message templating to enforce consistent messaging across commits.
  • Explain React hooks to a new developer as a recurring educational prompt.
  • Debug Bash permission errors template to standardize triage steps.
  • API quirks research prompt organized with structured inquiries and findings.

Frequently Asked Questions

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