Adaline Skills
Skills that guide AI coding agents to integrate with the Adaline platform — send traces, manage prompts, run evaluations, fetch deployments, and more. Compatible with Cursor, Claude Code, Codex, Windsurf, and 40+ other agents.
Install
npx (recommended)
npx skills add adaline/skills
Install a single skill:
npx skills add adaline/skills --skill adaline-logs
Preview available skills:
npx skills add adaline/skills --list
Install for specific agents:
npx skills add adaline/skills -a claude-code -a cursor -y
The CLI auto-detects installed agents and symlinks skills into the correct directory (.claude/skills/, .cursor/skills/, etc.).
Claude Code plugin
/plugin marketplace add adaline/skills
/plugin install skills
Manual
Clone the repo and copy skill folders into your agent's skills directory:
git clone https://github.com/adaline/skills.git
Then copy the skills you need:
- Claude Code:
.claude/skills/
- Cursor:
.cursor/skills/
- Codex:
.codex/skills/
Update
npx skills check # check for updates
npx skills update # update all installed skills
Configuration
When you have your Adaline credentials, set these environment variables:
export ADALINE_API_KEY=your-api-key # from Settings > API Keys in the dashboard
export ADALINE_PROJECT_ID=your-project-id # from the project sidebar in the dashboard
No credentials yet? Skills use placeholder values by default — you can start integrating now and replace them with real values once your account is ready. Sign up at https://app.adaline.ai/sign-up
Available Skills
| Skill | What it does |
|---|
| adaline-integration | High-level integration guide. Start here — helps you choose the right skills and approach (API, TypeScript SDK, Python SDK) for your setup. |
| adaline-logs | Send traces and spans to Adaline for AI agent observability. Covers REST API, TypeScript SDK, and Python SDK instrumentation. |
| adaline-deployments | Fetch deployed prompt snapshots at runtime. Use environment-based latest deployment lookup or pin a concrete deployment ID. |
| adaline-prompts | Create and manage prompts programmatically via the REST API. |
| adaline-datasets | Build and manage evaluation datasets — columns, rows, CSV import, dynamic columns. |
| adaline-evaluators | Create evaluators: LLM-as-a-judge, JavaScript, text-matcher, cost, latency, response-length. |
| adaline-evaluations | Run evaluations at scale, check status, analyze per-row results, cancel runs. |
| adaline-providers | List configured AI providers (OpenAI, Anthropic, Google, etc.) and available models. |
Start Here
Use adaline-integration first — it helps you choose which skills to adopt based on your runtime, codebase, and goals.
Recommended order:
adaline-logs — get observability firstadaline-deployments — fetch the active prompt snapshot in your appadaline-datasets + adaline-evaluators + adaline-evaluations — quality gatesadaline-providers — discover available models
Integration Approaches
| Approach | Best for | Skills that support it |
|---|
TypeScript SDK (@adaline/client) | Node.js/TypeScript apps | adaline-logs, adaline-deployments |
Python SDK (adaline-client) | Python apps | adaline-logs, adaline-deployments |
| REST API | Any language, serverless | All skills |
| Adaline Proxy (zero-code) | Quick start, simple apps | adaline-logs (see SKILL.md) |
Repository structure
skills/
adaline-integration/ # Master integration guide
adaline-logs/ # Traces and spans
adaline-deployments/ # Deployment fetching
adaline-prompts/ # Prompt management
adaline-datasets/ # Dataset management
adaline-evaluators/ # Evaluator creation
adaline-evaluations/ # Running evaluations
adaline-providers/ # Provider/model discovery
scripts/ # CI validation
.claude-plugin/ # Plugin config for distribution
Links
