> ## Documentation Index > Fetch the complete documentation index at: https://docs.cloudthinker.io/llms.txt > Use this file to discover all available pages before exploring further. # AI Agents > Meet the five specialized CloudThinker agents and choose the right one for cost, security, database, and Kubernetes work CloudThinker ships five specialized agents that analyze, report on, and act across your cloud environment. Each agent owns a domain, keeps persistent memory of your infrastructure, and coordinates with the others on cross-domain work. ## The agent roster | Agent | Role | Best for | | ---------------------------------- | ------------------- | --------------------------------------------------------------------------------------- | | [**Alex**](/guide/agents/alex) | Cloud Engineer | Cost analysis, infrastructure optimization, multi-cloud architecture, reserved capacity | | [**Oliver**](/guide/agents/oliver) | Security Engineer | Compliance audits, vulnerability assessment, IAM reviews, threat detection | | [**Tony**](/guide/agents/tony) | Database Engineer | Query optimization, performance tuning, index recommendations, capacity planning | | [**Kai**](/guide/agents/kai) | Kubernetes Engineer | Cluster health, pod right-sizing, autoscaling, RBAC audits, troubleshooting | | [**Anna**](/guide/agents/anna) | General Manager | Multi-agent coordination, cross-domain projects, executive reporting | Want a different tone, restricted access, or a fully custom agent? See [Customize agents](/guide/agents/customize). ## Choose the right agent | You need | Mention | | ------------------------------------- | --------- | | Cloud costs are too high | `@alex` | | A security audit or compliance report | `@oliver` | | A slow database diagnosed | `@tony` | | Kubernetes cluster issues resolved | `@kai` | | A problem that spans multiple domains | `@anna` | | A starting point when you're not sure | `@anna` | Anna dispatches work to the other agents, so she is the safe default for incident investigations and cross-domain projects. ## Talk to agents Talk to agents in plain language. The full pattern is: ```text theme={null} @agent #tool your request ``` * **`@agent`** — who does the work: `@alex` (cloud), `@oliver` (security), `@tony` (database), `@kai` (Kubernetes), `@anna` (coordination). * **`#tool`** *(optional)* — the output you want: `#dashboard`, `#report`, `#recommend`, `#alert`, `#chart`, `#kb`. * **Your request** — what you need, in your own words. Add any context inline. See the [CloudThinker Language reference](/guide/language) for the full syntax. ```text theme={null} @alex #dashboard build an EC2 cost dashboard for the last 30 days @oliver #report audit security groups open to the internet on ports 22, 3306, and 5432 @anna #report run a quarterly infrastructure review across cost, security, and Kubernetes ``` ## How agents work 1. **Read your prompt** — the agent parses your mention, the optional tool tag, and your instruction. 2. **Query your connections** — the agent reads the [connections](/guide/connections/overview) you've configured: AWS, Azure, GCP, Kubernetes clusters, databases, and more. 3. **Correlate data across sources** — Alex cross-references CloudWatch utilization with Cost Explorer data; Tony reads execution plans alongside query frequency. 4. **Deliver the output you asked for** — a dashboard, report, prioritized recommendations, or an alert. 5. **Act within its autonomy mode** — in Manual mode the agent waits for your [approval](/guide/approval) before executing changes. Every action is logged with an audit trail. ## Autonomy Each agent runs in one of two modes, configurable per agent: | Mode | What happens | | ---------- | ---------------------------------------------------------------------------------- | | **Manual** | The agent proposes the action and waits for a person to approve it before running. | | **Auto** | The agent runs the action on its own and reports the result. | See [Auto Mode](/guide/auto-mode) for how Auto executions are scoped, guarded, and audited. ## Memory and context Agents get more accurate over time because they retain what they learn about your environment: | Memory type | What it retains | | ----------- | ----------------------------------------------------------------------------------- | | Episodic | Past analyses and decisions, such as resources you've exempted from recommendations | | Working | Context within the current conversation thread | | Semantic | Patterns learned about your infrastructure over time | | File | Documents, runbooks, and [knowledge base](/guide/knowledge) entries | ## When agents activate Agents become available as you add the relevant connections: | Agent | Available when | | ---------- | ---------------------------------------------------------- | | **Anna** | Always — no connections required | | **Alex** | An AWS, Azure, or GCP connection is added | | **Oliver** | An AWS, Azure, or GCP connection is added | | **Tony** | A PostgreSQL, MySQL, or other database connection is added | | **Kai** | A Kubernetes cluster connection is added | ## Next steps Tune personality, attach connections, and build fully custom agents The complete `@agent #tool instruction` syntax reference Connect cloud providers, databases, and Kubernetes clusters Understand how autonomous execution is scoped and audited