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.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionaiconfig-createExecute the skills CLI command in your project's root directory to begin installation:
Fetches aiconfig-create from launchdarkly/agent-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate aiconfig-create. Access via /aiconfig-create in your agent's command palette.
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.
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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.
ai-configs:write permission or MCP serveraiconfig-projects skill if needed)LAUNCHDARKLY_API_KEY, LAUNCHDARKLY_API_TOKEN, LD_API_KEY~/.claude/config.json → mcpServers.launchdarkly.env.LAUNCHDARKLY_API_KEYBefore creating, identify what you're building:
| 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.
Follow API Quick Start for curl examples:
POST /projects/{projectKey}/ai-configs (key, name, mode)POST /projects/{projectKey}/ai-configs/{configKey}/variations (instructions or messages, modelConfigKey, model.parameters)aiconfig-tools skill)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:
Report results:
https://app.launchdarkly.com/projects/{projectKey}/ai-configs/{configKey}{Provider}.{model-id} (e.g., OpenAI.gpt-4o) for models to show in UIaiconfig-tools skill), then attached via PATCH/ai-tools, NOT /ai-configs/tools| 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-tools — Create tools before attachingaiconfig-variations — Add more variations for experimentationaiconfig-update — Modify configs based on learningsPrerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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aiconfig-create fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Registry listing for aiconfig-create matched our evaluation — installs cleanly and behaves as described in the markdown.
aiconfig-create reduced setup friction for our internal harness; good balance of opinion and flexibility.
aiconfig-create fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
We added aiconfig-create from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
I recommend aiconfig-create for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
aiconfig-create has been reliable in day-to-day use. Documentation quality is above average for community skills.
Useful defaults in aiconfig-create — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Solid pick for teams standardizing on skills: aiconfig-create is focused, and the summary matches what you get after install.
We added aiconfig-create from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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