aiconfig-create

You're using a skill that will guide you through setting up AI configuration in your application. Your job is to explore the codebase to understand the use case and stack, choose agent vs completion mode, create the config following the right path, and verify it works.

launchdarkly/agent-skills|Updated Apr 8, 2026

Works with

Claude CodeCursorClineWindsurfCodex

Installation Guide

Select your AI agent

How to use aiconfig-create on Cursor

AI-first code editor with Composer

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

›Cursor installed and configured on your machine
›Node.js 16+ with npm — verify with node --version
›Active project directory where you want to add aiconfig-create

Run the install command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/launchdarkly/agent-skills --skill aiconfig-create

Fetches aiconfig-create from launchdarkly/agent-skills and configures it for Cursor.

Select Cursor when prompted

The CLI shows a list of agents. Use arrow keys and space to select Cursor:

◆ Which agents do you want to install to?

│

│ ── Universal (.agents/skills) ────────────────

│ · Cline · Codex · Goose · Windsurf

│ ●Cursor(selected)

│ · Cursor · Aider · Continue

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/aiconfig-create

Restart Cursor to activate aiconfig-create. Access via /aiconfig-create in your agent's command palette.

⚠

Security Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.

›View source on GitHub ›Skills CLI docs ›About Cursor ›What are agent skills?

Documentation

List & Monetize Your Skill

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

✓

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

✓

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

✓

Improve work quality by 30-40% with less effort

Core Principles

Understand the Use Case First: Know what you're building before choosing a mode

Choose the Right Mode: Agent mode vs completion mode depends on your framework and needs

Two-Step Creation: Create config first, then create variations (model, prompts, parameters)

Verify via API: The agent fetches the config to confirm it was created correctly

Workflow

Step 1: Understand Your Use Case

Before creating, identify what you're building:

What framework? LangGraph, LangChain, CrewAI, OpenAI SDK, Anthropic SDK, custom

What does the AI need? Just text, or tools/function calling?

Agent or completion? See decision below

Step 2: Choose Agent vs Completion Mode

Your Need

Mode

Persistent instructions across interactions

Agent

LangGraph, CrewAI, AutoGen

Agent

Direct OpenAI/Anthropic API calls

Completion

Full control of message structure

Completion

One-off text generation

Completion

Both modes support tools. Agent mode: single instructions string. Completion mode: full messages array.

Step 3: Create the Config

Follow API Quick Start for curl examples:

Create config — POST /projects/{projectKey}/ai-configs (key, name, mode)

Create variation — POST /projects/{projectKey}/ai-configs/{configKey}/variations (instructions or messages, modelConfigKey, model.parameters)

Attach tools — After creation, PATCH variation to add tools (see aiconfig-tools skill)

Step 4: Verify

After creation, verify the config:

Fetch via API:

curl -X GET "https://app.launchdarkly.com/api/v2/projects/{projectKey}/ai-configs/{configKey}" \
  -H "Authorization: {api_token}" -H "LD-API-Version: beta"

Confirm:

Config exists with correct mode
Variations have model names (not "NO MODEL")
modelConfigKey is set
Parameters are present

Report results:

✓ Config created with correct structure
✓ Variations have models assigned
⚠️ Flag any missing model or parameters
Provide config URL: https://app.launchdarkly.com/projects/{projectKey}/ai-configs/{configKey}

Situation

Action

Config already exists

Ask if user wants to update instead

Variation shows "NO MODEL"

PATCH variation with modelConfigKey and model

Invalid modelConfigKey

Use values from model-configs API

aiconfig-create

Installation Guide

How to use aiconfig-create on Cursor

Prerequisites

Run the install command

Select Cursor when prompted

Verify installation

Security Notice

Documentation

List & Monetize Your Skill

Use Cases

Task Automation & Efficiency

Knowledge Enhancement

Quality Improvement

Install Skill

Create AI Config

Prerequisites

Core Principles

API Key Detection

Workflow

Step 1: Understand Your Use Case

Step 2: Choose Agent vs Completion Mode

Step 3: Create the Config

Step 4: Verify

Important Notes

Edge Cases

What NOT to Do

Related Skills

References

Implementation Guide

Best Practices

When to Use This

Learning Path

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Reviews

Discussion