Chapter 13: Building a Prompt Library: Governance + Quality Bar
February 9, 2026
·
2 min read

Series: LLM Development Guide
Chapter 13 of 15
Previous: Chapter 12: Templates + Checklists: The Copy/Paste Kit
Next: Chapter 14: Worked Example: Creating a Helm Chart From a Reference Chart
What you’ll be able to do
You’ll be able to build a prompt library that doesn’t turn into a junk drawer:
- Organize prompts by task type.
- Define a consistent prompt entry format.
- Set a contribution and maintenance policy.
TL;DR
- A prompt library is a shared collection of prompts proven in real usage.
- Require prereqs, recommended model tier, expected output, and common failure fixes.
- Assign maintainers.
- Version prompts with a changelog.
Table of contents
Library structure
A simple layout that scales:
prompt-library/
README.md
CONTRIBUTING.md
planning/
implementation/
testing/
review/
debugging/
Keep it boring. Avoid inventing new categories every week.
Prompt entry template
Require a consistent format so prompts are reusable:
# <Task Name>
## When to use
## Prerequisites
-
## Recommended model tier
## The prompt
## Customization points
## Expected output
## Common issues and fixes
## Examples
## Changelog
- YYYY-MM-DD: <what changed>
Contribution guidelines
Set a quality bar:
- A prompt must have been used successfully multiple times.
- It must specify required reference files.
- It must include verification.
- It must include common failure modes and fixes.
A contribution checklist:
- Used successfully 3+ times.
- Another person can run it with the listed prereqs.
- Changelog updated.
Governance
If nobody owns it, it rots.
Assign 1 to 2 maintainers to:
- Review new prompts.
- De-duplicate similar prompts.
- Archive prompts that no longer work.
- Run a quarterly cleanup.
Verification
Bootstrap the skeleton:
mkdir -p prompt-library/{planning,implementation,testing,review,debugging}
touch prompt-library/README.md
touch prompt-library/CONTRIBUTING.md
cat > prompt-library/planning/new-task.md <<'MD'
# New Task Planning
## When to use
## Prerequisites
## Recommended model tier
## The prompt
## Verification
MD
Expected result:
- You have a real place to put prompts that worked, with enough structure to keep it maintainable.
Continue -> Chapter 14: Worked Example: Creating a Helm Chart From a Reference Chart
Authors
DevOps Architect · Applied AI Engineer
I’ve spent 20 years building systems across embedded firmware, security platforms, fintech, and enterprise architecture. Today I focus on production AI systems in Go — multi-agent orchestration, MCP server ecosystems, and the DevOps platforms that keep them running. I care about systems that work under pressure: observable, recoverable, and built to last.