Prompt Library & LLM Testing Workflow

Prompt engineering is becoming one of the most important skills in tech - and one of the least supported by existing tools. You're writing prompts, testing them across models, tracking which versions perform best, running evaluations, and iterating constantly. But your prompt library lives in scattered Google Docs, your test results are in spreadsheets, and your team's review process happens in Slack threads that disappear into the void.

t0ggles is the project management tool that gives prompt engineers everything they need to manage prompt versions, organize testing workflows, and track evaluations in one place. Use custom properties to log model versions, temperature settings, and evaluation scores. Track prompt iterations with task dependencies so you never lose the chain of improvements. All for $5/user/month with every feature included.

#The Challenge: Why Prompt Engineers Need Better Tools

Prompt engineering looks simple from the outside - you're "just writing text." In practice, it's a complex iterative process with unique management challenges:

Version control is a mess. You write a prompt, test it, tweak it, test again. After twenty iterations, you can't remember which version produced the best results or what you changed between v7 and v12. File naming conventions break down fast when you're iterating multiple times per day.

Testing across models requires tracking. The same prompt behaves differently on GPT-4o, Claude, Gemini, and Llama. You need to test systematically, record results for each model, and compare performance. Without structure, you end up retesting combinations you've already tried.

Team reviews lack structure. When multiple people work on prompts - writers, developers, domain experts - the feedback loop gets chaotic. Comments are scattered across tools. It's unclear who has reviewed what, which feedback has been incorporated, and which version is the current "production" prompt.

Evaluation metrics aren't connected to iterations. You run evals and get scores, but those scores live separately from the prompts that generated them. Connecting "this prompt version scored 87% on accuracy" to the actual prompt text requires manual cross-referencing.

#How t0ggles Helps Prompt Engineers Work Systematically

#Custom Properties: Track Every Variable

Custom properties turn each task into a structured prompt record. Add fields specific to your prompt engineering workflow:

• Model (select): GPT-4o, Claude 3.5, Gemini Pro, Llama 3.1
• Temperature (number): 0.0 - 2.0
• Version (number): Track iteration count
• Eval Score (number): Accuracy, relevance, or custom metric
• Status (select): Draft, Testing, Reviewed, Production, Deprecated
• Use Case (text): What this prompt is designed for
• Token Count (number): Input/output token usage

Filter and sort by any property. Want to see all prompts with eval scores above 85%? One click. Need all GPT-4o prompts sorted by temperature? Done. The board becomes a living prompt library with built-in analytics.

#Task Descriptions: Your Prompt Repository

Each task's description field holds the full prompt text. With t0ggles' rich text editor and code blocks, you can format prompts with proper syntax highlighting, include system messages, few-shot examples, and output format specifications.

Comments on each task capture the iteration history - what you changed and why. When you revisit a prompt months later, the full context is right there: the original version, every modification, the reasoning behind each change, and the eval results at each stage.

#Dependencies: Track Prompt Iteration Chains

Task dependencies model the evolution of your prompts. When you create an improved version, link it as a successor to the previous version. The dependency chain shows the full lineage:

1. v1: Basic summarization prompt (initial version)
2. v2: Added output format constraints (depends on v1)
3. v3: Few-shot examples added (depends on v2)
4. v4: Chain-of-thought reasoning (depends on v3)

The Gantt view visualizes the iteration timeline. You can see at a glance how long each iteration took, where testing bottlenecks occurred, and which branches of experimentation led to the best results.

#Multi-Project Boards: Organize by Use Case

Prompt engineers typically manage prompts across multiple products, features, or clients. t0ggles multi-project boards let you organize everything on one board:

• Customer Support Prompts project - classification, response generation, escalation
• Content Generation project - blog posts, social media, email campaigns
• Data Extraction project - parsing, summarization, entity recognition
• Code Assistance project - code review, documentation, refactoring

Focus Mode filters to just one project when you need to dive deep. The combined view shows all active prompt work across projects, so you never lose sight of the bigger picture.

#MCP Server: AI-Assisted Prompt Management

The MCP server connects your AI tools directly to your prompt library on t0ggles. Your coding agent can:

• Pull the current production prompt from the board before using it
• Log test results as comments on prompt tasks
• Create new iteration tasks when a prompt needs improvement
• Update eval scores after running automated evaluations

This creates a feedback loop where the AI that uses your prompts also helps manage and improve them.

#Board Automations: Streamline the Review Process

Board automations keep your prompt workflow moving:

• When a prompt moves to "Testing", notify the QA reviewer
• When eval score drops below threshold, auto-tag as "needs attention"
• When a prompt is marked "Production", create a deployment checklist task
• Auto-assign new prompts to the team's prompt reviewer

The review process runs consistently without manual coordination.

#Prompt Engineering Workflows In t0ggles

#Prompt Development Cycle

Create a task for each new prompt with statuses: Draft, Testing, Review, Production, Deprecated. Write the initial prompt in the task description. Add custom properties for model, temperature, and target metrics.

Start testing. Log each test run as a comment with the results. Update the eval score property as you iterate. When you're happy with performance, move the task to "Review" for team feedback. Reviewers leave comments directly on the task - no switching to Slack or email.

After approval, move to "Production" and lock in the version. If you need to iterate later, create a new task linked as a successor, preserving the full history.

#A/B Testing Workflow

Create two tasks for competing prompt versions - same use case, different approaches. Add a "Variant" custom property (A or B). Run both through your evaluation pipeline and log results.

The board makes comparison easy: filter by use case, sort by eval score, and see which variant wins. The losing variant moves to "Deprecated" with a comment explaining what the winner did better - building institutional knowledge for future prompt development.

#Cross-Model Evaluation

Create a project called "Model Comparison" with tasks for each prompt-model combination. Custom properties track the model, prompt version, and evaluation metrics. Dependencies link the same prompt tested across different models.

The list view sorted by eval score gives you a leaderboard. Filter by model to see which prompts work best on each platform. This systematic approach replaces ad-hoc testing with structured, reproducible comparisons.

#What Prompt Engineers Need vs What t0ggles Delivers

What You Need	How t0ggles Delivers
Organized prompt library	Tasks with rich text descriptions, code blocks, and version tracking
Variable tracking per prompt	Custom properties for model, temperature, eval scores, token usage
Iteration history	Task dependencies chain prompt versions with full comment history
Team review process	Structured status workflow with comments and notifications
Multi-project organization	Projects per use case with Focus Mode for filtered views
Evaluation tracking	Custom number properties for scores, sortable and filterable
AI-powered management	MCP server for automated prompt library interaction
Automation	Board automations for review workflows and notifications

#Why Choose t0ggles for Prompt Engineering

vs spreadsheets: Spreadsheets can track variables but can't hold full prompt text, manage review workflows, or model dependencies between versions. t0ggles combines the structured data of a spreadsheet with the workflow management prompts need.

vs Notion: Notion databases can store prompts but lack real task management - no dependencies, no Gantt view, no MCP integration for AI-assisted management.

vs dedicated prompt tools: Most prompt management platforms are expensive and locked to specific models. t0ggles is model-agnostic, costs $5/user/month, and handles any prompt workflow you design.

vs Jira: Jira's heavyweight processes add friction to the rapid iteration that prompt engineering requires. t0ggles is fast, clean, and adapts to your workflow instead of forcing you into one.

#Simple, Affordable Pricing

One plan. One price. Every feature.

$5 per user per month (billed annually) includes:

• Unlimited boards, projects, tasks, notes, and files
• Custom properties for prompt metadata tracking
• Task dependencies with Gantt view
• MCP server for AI-assisted prompt management
• Board automations
• Rich text editor with code blocks for prompt formatting
• All integrations (GitHub, Zapier, Google Calendar)

No feature tiers. No per-seat surprises.

14-day free trial - start building your prompt library today.

#Get Started Today

Prompt engineering deserves the same structured workflow that software development has had for years. t0ggles gives you the version tracking, evaluation management, and team collaboration tools to move from ad-hoc prompting to systematic prompt development.

Start your free trial and bring order to your prompt engineering workflow.