> ## 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. # CloudThinker Language > Look up the @agent #tool syntax: agent mentions, tool tags, context modifiers, and prompt patterns for every agent CloudThinker Language is the structured prompt syntax that works identically across every agent, in chat, [Slack](/guide/slack-integration), and automations. Mention an agent, tag the output you want, then write your instruction in plain language. ## Syntax Every prompt follows one canonical form: ```text theme={null} @agent #tool instruction ``` | Component | Required | Description | | ------------- | -------- | ------------------------------------------------------------------------------------------------------- | | `@agent` | Yes | Routes the request to a specific agent. Mention several agents for cross-domain work. | | `#tool` | No | Output format or capability. Place it immediately after the mention; combine tags for multiple outputs. | | `instruction` | Yes | What you want, in your own words — include scope, timeframe, thresholds, and constraints inline. | ## Agent mentions | Mention | Role | Best for | | --------- | ------------------- | ---------------------------------------------------------------- | | `@alex` | Cloud Engineer | Cost analysis, resource optimization, multi-cloud infrastructure | | `@oliver` | Security Engineer | Audits, vulnerability scans, IAM, compliance | | `@tony` | Database Engineer | Query optimization, performance tuning, backups | | `@kai` | Kubernetes Engineer | Cluster management, pod optimization, scaling | | `@anna` | General Manager | Multi-agent coordination, executive reporting | See the [agent reference](/guide/agents) for each agent's full capabilities. ## Tool tags | Tag | Output | Example | | ------------ | ----------------------------------------------------------------- | ---------------------------------------------------- | | `#dashboard` | Interactive visualizations for monitoring and presentations | `@alex #dashboard monthly cost trends with forecast` | | `#report` | Detailed analysis documents with findings and evidence | `@oliver #report SOC 2 compliance assessment` | | `#recommend` | Prioritized, actionable recommendations with implementation steps | `@tony #recommend index changes for slow queries` | | `#alert` | Monitoring notifications on the conditions you define | `@kai #alert on pod OOMKilled events` | | `#chart` | Standalone data visualizations | `@alex #chart spending by service` | | `#kb` | Knowledge base search across your organization's docs | `@alex #kb cloud governance policies` | Combine tags when you want more than one output: `@alex #dashboard #recommend cost optimization opportunities`. ## Context modifiers Add context inside the instruction to narrow scope and improve accuracy. | Type | Examples | | --------- | --------------------------------------------------------------------- | | Timeframe | `over the last 30 days`, `since January`, `in the last 24 hours` | | Scope | `in us-east-1`, `on the production cluster`, `on the orders database` | | Threshold | `with CPU below 15%`, `costing over $1,000/month`, `P95 above 500ms` | | Exclusion | `excluding production-tagged resources`, `except backup buckets` | | Priority | `prioritizing quick wins`, `critical severity first` | ## Prompt patterns | Pattern | Form | Example | | ----------- | -------------------------------------------- | --------------------------------------------------------------------- | | Analyze | `@agent #tool analyze ` | `@alex analyze EC2 spending by instance family over the last quarter` | | Audit | `@agent #tool audit for ` | `@oliver audit S3 buckets for public access and encryption` | | Optimize | `@agent #recommend ` | `@kai #recommend HPA policies for variable workloads` | | Investigate | `@agent investigate ` | `@tony investigate slow query performance on the orders table` | | Coordinate | `@anna coordinate with ` | `@anna coordinate quarterly review with @alex @oliver @tony @kai` | In Slack, the same syntax works with a bot prefix: `@CloudThinker alex what's our AWS spend this week?` — see [Slack integration](/guide/slack-integration). ## Examples Direct requests — pick the agent, tag the output, state the target: ```text theme={null} @alex #dashboard AWS spending by service and region @oliver #report SOC 2 compliance assessment with evidence @tony #recommend index changes for queries slower than 500ms ``` Stack context modifiers to make results precise and safe to act on: ```text theme={null} @alex #recommend right-sizing for EC2 instances in us-east-1 with CPU below 15% over the last 30 days, excluding production-tagged resources ``` Mention multiple agents for cross-domain problems: ```text theme={null} @alex @tony investigate the cost spike on database infrastructure last week @anna coordinate security remediation with @oliver leading and @alex @kai supporting ``` Refine progressively — start broad, then drill into what the agent finds: ```text theme={null} @alex #dashboard cloud spending trends @alex #chart November cost spike broken down by service @alex #recommend RDS optimization prioritizing underutilized instances ``` Be specific. `@alex #recommend right-sizing for EC2 in us-east-1 with CPU below 15%` gets an actionable answer; `@alex check our servers` gets a clarifying question. ## Related Each agent's expertise, capabilities, and prompt patterns in depth What #dashboard, #report, #recommend, and other tool tags produce Pre-built operations ready to run with this syntax Use the same syntax in Slack with the @CloudThinker prefix