An autonomous monitoring skill for real-time anomaly detection and operational efficiency across multi-cloud environments.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install anodot
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install anodot using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Anodot?
Anodot is a sophisticated autonomous monitoring platform that leverages machine learning to detect anomalies in time series data. By integrating this capability via Openclaw Skills, developers can empower their AI agents to identify and resolve critical issues in real-time, effectively minimizing revenue loss and boosting operational efficiency across industries like e-commerce, finance, and telecommunications.
This skill provides a bridge to Anodot’s vast ecosystem, allowing agents to interact with metrics, dashboards, alerts, and notebooks. It also offers extensive support for monitoring cloud infrastructure costs across AWS, Azure, and GCP, making it an essential tool for maintaining both performance and financial health in complex digital environments.
Anodot Use Cases
- Identifying sudden drops in e-commerce conversion rates or revenue through real-time anomaly detection.
- Monitoring and alerting on multi-cloud infrastructure costs to prevent budget overruns in AWS, Azure, or GCP.
- Automating incident management workflows by syncing Anodot alerts with tools like Jira, Slack, or PagerDuty.
- Analyzing complex time series data from databases like Snowflake or BigQuery to find hidden operational patterns.
How Anodot Works
- Install the required CLI to manage Openclaw Skills on your local or headless environment.
- Authenticate the agent with the platform to handle secure credential management.
- Establish a connection to the Anodot instance using a normalized domain URL.
- Search for specific monitoring actions using natural language intents to find the most efficient tools.
- Execute actions or use the built-in proxy to query the Anodot API directly with automated header and token management.
Anodot Setup
To begin using this skill within the Openclaw Skills ecosystem, install the Membrane CLI:
npm install -g @membranehq/cli@latest
Authenticate your agent session:
membrane login --tenant --clientName=openclaw
Create a secure connection to your Anodot account:
membrane connection ensure "https://anodot.com" --json
Anodot Data Schema & Taxonomy
The Anodot skill organizes its data and metadata around monitoring and cloud resource entities. Key data types include:
| Entity | Description |
|---|---|
| Metrics | Time series data points and metric groups used for anomaly detection. |
| Alerts | Configurable notifications triggered when anomalies exceed defined segments. |
| Cost Entities | Financial records associated with cloud accounts (AWS, Azure, GCP). |
| Integrations | Metadata for third-party connections like Snowflake, Datadog, or Slack. |
| Sources | Configuration for data ingestion from S3 buckets, databases, or scripts. |
Anodot Advanced Features
- Multi-cloud cost tracking support for granular financial oversight across AWS, Azure, and GCP.
- Seamless proxy requests that automatically inject authentication headers and manage transparent credential refreshes.
- Natural language action discovery to identify pre-built workflows, reducing token usage and development time.
- Support for over 100+ integration types, ranging from security platforms like CrowdStrike to devops tools like Kubernetes.
SKILL.md
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