Prompt

CloudThinker uses a natural language interface enhanced with structured syntax. This guide is the definitive reference for communicating effectively with agents.

Syntax Overview

Every CloudThinker prompt follows this structure:

@agent [instruction] [#tool] [context]

Component	Required	Description
`@agent`	Yes	Routes the request to a specific agent
`instruction`	Yes	What you want the agent to do
`#tool`	No	Output format or capability to use
`context`	No	Constraints, timeframes, scope

Agent Mentions

Use @ to direct requests to specific agents:

Agent	Expertise	When to Use
`@alex`	Cloud infrastructure, cost, performance	Cost analysis, resource optimization, multi-cloud
`@oliver`	Security, compliance, threats	Audits, vulnerability scans, IAM, compliance
`@tony`	Databases, queries, analytics	Query optimization, performance tuning, backups
`@kai`	Kubernetes, containers, orchestration	Cluster management, pod optimization, scaling
`@anna`	Coordination, strategy, reporting	Multi-agent projects, executive reports, complex ops

Single Agent

@alex analyze EC2 spending trends over the last quarter
@oliver audit all S3 buckets for public access
@tony identify queries with execution time >2 seconds
@kai check pod resource utilization in production namespace

Multi-Agent Collaboration

Address multiple agents for complex problems:

@alex @tony investigate cost spike on database infrastructure
@oliver @kai audit Kubernetes RBAC and network policies
@anna coordinate security remediation across @oliver @alex @kai

Tool Commands

Use # to specify output format or invoke specific capabilities:

Tool	Purpose	Example
`#dashboard`	Interactive visualizations	`@alex #dashboard monthly cost trends`
`#report`	Detailed analysis documents	`@oliver #report SOC 2 compliance assessment`
`#recommend`	Actionable recommendations	`@tony #recommend index optimizations`
`#alert`	Monitoring notifications	`@kai #alert when node CPU >80%`
`#chart`	Data visualizations	`@alex #chart spending by service`
`#kb`	Knowledge base search	`@alex #kb AWS cost optimization policies`

Tool Combinations

Combine tools with agent mentions:

@alex #dashboard #recommend cost optimization opportunities
@oliver #report #alert security findings requiring immediate action
@tony #dashboard database performance with #alert on P95 >500ms

Tool-Specific Patterns

#dashboard
#report
#recommend
#alert
#kb

Creates interactive visualizations for monitoring and presentation.

# Cost dashboards
@alex #dashboard AWS spending by service and region
@alex #dashboard monthly cost trends with forecast

# Performance dashboards
@tony #dashboard query latency P50/P95/P99 over time
@kai #dashboard cluster resource utilization by node

# Security dashboards
@oliver #dashboard compliance status across frameworks
@oliver #dashboard security findings by severity

Generates comprehensive analysis documents with findings and recommendations.

# Compliance reports
@oliver #report SOC 2 Type II assessment with evidence
@oliver #report GDPR data processing audit

# Optimization reports
@alex #report quarterly cost optimization summary
@tony #report database performance analysis with recommendations

# Executive reports
@anna #report infrastructure health for board presentation

Produces prioritized, actionable recommendations with implementation steps.

# Cost recommendations
@alex #recommend reserved instance purchases based on usage
@alex #recommend resources for right-sizing or termination

# Performance recommendations
@tony #recommend index changes for slow queries
@kai #recommend HPA policies for variable workloads

# Security recommendations
@oliver #recommend security group rule changes

Configures monitoring alerts for proactive notification.

# Cost alerts
@alex #alert when daily spend exceeds $5,000
@alex #alert on resources with >50% cost increase week-over-week

# Performance alerts
@tony #alert when query P95 latency exceeds 500ms
@kai #alert on pod OOMKilled events or node pressure

# Security alerts
@oliver #alert on security group changes allowing 0.0.0.0/0
@oliver #alert on failed login attempts >10 per minute

Searches your organization’s knowledge base.

# Policy searches
@alex #kb cloud governance policies
@oliver #kb:security-policies incident response procedures

# Best practices
@tony #kb PostgreSQL optimization best practices
@kai #kb Kubernetes deployment standards

Context Modifiers

Add context to narrow scope and improve accuracy:

Timeframes

@alex analyze spending over the last 30 days
@alex compare costs: last month vs same period last year
@tony identify slow queries from the past week
@oliver find security group changes in the last 24 hours

Scope

@alex analyze EC2 instances in us-east-1 region
@oliver audit production environment security groups
@tony check performance on the orders database
@kai review staging cluster resource allocation

Thresholds

@alex identify instances with CPU utilization <15%
@tony find queries with execution time >2 seconds
@kai flag pods requesting >2GB memory but using <500MB
@oliver find IAM roles with >50 attached policies

Exclusions

@alex recommend terminations excluding production-tagged resources
@oliver audit all buckets except backup-* prefixed ones
@tony analyze all databases excluding read replicas

Priorities

@alex #recommend cost savings prioritizing quick wins under 30 days
@oliver identify vulnerabilities, critical severity first
@tony optimize queries prioritizing those running >100x daily

Combined Context

@alex analyze EC2 instances in us-east-1
  with CPU <20% over last 30 days
  excluding production-critical
  #recommend right-sizing with projected savings

@oliver audit security groups in production
  for public access on ports 22, 3389, 3306
  #report with remediation timeline
  prioritizing internet-facing resources

Prompt Patterns

Pattern 1: Analysis Request

@agent analyze [target] [context]

@alex analyze EC2 spending by instance family over last quarter
@tony analyze query patterns on production PostgreSQL cluster
@kai analyze pod scheduling efficiency across all nodes
@oliver analyze IAM permission usage for service accounts

Pattern 2: Audit Request

@agent audit [target] for [criteria]

@oliver audit S3 buckets for public access and encryption
@oliver audit IAM policies for privilege escalation paths
@alex audit infrastructure for unused or orphaned resources
@kai audit RBAC configuration against least-privilege principles

Pattern 3: Optimization Request

@agent optimize/recommend [target] [constraints]

@alex recommend cost optimizations maintaining 99.9% availability
@tony recommend index changes for queries >500ms execution time
@kai optimize pod resource requests based on actual utilization

Pattern 4: Investigation Request

@agent investigate [issue] [scope]

@alex investigate cost spike on database services last week
@tony investigate slow query performance on orders table
@kai investigate pod crash loops in payment namespace
@oliver investigate failed authentication attempts from unusual IPs

Pattern 5: Coordination Request

@anna coordinate [project] with @agents [scope]

@anna coordinate AWS to GCP migration with @alex @tony @kai
@anna coordinate security remediation with @oliver leading, @alex @kai supporting
@anna coordinate quarterly review: @alex cost, @oliver security, @tony databases, @kai containers

Advanced Techniques

Start broad, then drill down based on findings:

# Step 1: Broad overview
@alex #dashboard cloud spending trends

# Step 2: Identify problem area
@alex which services drove the November cost spike?

# Step 3: Deep dive
@alex break down RDS costs by instance type and utilization

# Step 4: Actionable recommendation
@alex #recommend RDS optimization prioritizing underutilized instances

Comparative Analysis

Ask agents to compare options:

@alex compare reserved instances vs savings plans for our EC2 usage pattern

@tony compare these approaches for database scaling:
  1. Read replicas
  2. Sharding by customer_id
  3. Migration to Aurora Serverless
  Include: cost, complexity, performance impact

@oliver compare SOC 2 vs ISO 27001 based on our customer requirements

Conditional Logic

Apply business rules to recommendations:

@alex #recommend instance right-sizing where:
  - CPU utilization <20% for >14 days
  - Not tagged as burst-capable
  - Not in auto-scaling groups
  - Savings >$50/month

@oliver prioritize security findings:
  - Critical: internet-exposed + known CVE
  - High: production + public access
  - Medium: everything else

Structured Requests

For complex requirements, use structured format:

@tony optimize database performance:
  Target: production PostgreSQL cluster
  Focus: queries running >100x daily with >500ms P95
  Constraints:
    - No schema changes requiring downtime
    - Maintain read replica compatibility
  Output: #recommend with implementation order and rollback plan

Slack Integration

In Slack, prefix with @CloudThinker:

@CloudThinker alex what's our AWS spending this week?
@CloudThinker oliver any critical security findings?
@CloudThinker tony why are queries slow on production?
@CloudThinker kai check EKS cluster health

All syntax works identically in Slack—just add the @CloudThinker prefix.

Quick Reference

Agents

Mention	Role	Best For
`@alex`	Cloud Engineer	Cost, infrastructure, multi-cloud
`@oliver`	Security Pro	Compliance, vulnerabilities, IAM
`@tony`	Database Engineer	Queries, performance, analytics
`@kai`	K8s Engineer	Containers, clusters, orchestration
`@anna`	General Manager	Coordination, strategy, reports

Tools

Command	Output	Use Case
`#dashboard`	Interactive viz	Monitoring, presentations
`#report`	Document	Compliance, deep analysis
`#recommend`	Action items	Implementation guidance
`#alert`	Notifications	Proactive monitoring
`#chart`	Visualization	Data trends
`#kb`	Knowledge search	Policy lookup

Context Keywords

Type	Examples
Time	`over last 30 days`, `since January`, `past week`
Scope	`in us-east-1`, `on production`, `for staging cluster`
Threshold	`with CPU <20%`, `costing >$1000/month`, `>500ms latency`
Exclusion	`excluding production`, `except backup buckets`
Priority	`prioritizing quick wins`, `critical first`

Best Practices

Be Specific

Good: @alex analyze EC2 in us-east-1 with <15% CPU over 30 daysAvoid: @alex check our servers

Provide Context

Include environment, timeframe, and constraints for accurate results

Use Right Agent

Match the request to agent expertise—security to Oliver, databases to Tony

Choose Right Tool

#dashboard for visuals, #report for documents, #recommend for actions

Next Steps

Agent Reference

Deep dive into each agent’s capabilities and patterns

Operations Hub

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Infrastructure

Setup

Use Cases

Reference

​Prompt

​Syntax Overview

​Agent Mentions

​Single Agent

​Multi-Agent Collaboration

​Tool Commands

​Tool Combinations

​Tool-Specific Patterns

​Context Modifiers

​Timeframes

​Scope

​Thresholds

​Exclusions

​Priorities

​Combined Context

​Prompt Patterns

​Pattern 1: Analysis Request

​Pattern 2: Audit Request

​Pattern 3: Optimization Request

​Pattern 4: Investigation Request

​Pattern 5: Coordination Request

​Advanced Techniques

​Progressive Refinement

​Comparative Analysis

​Conditional Logic

​Structured Requests

​Slack Integration

​Quick Reference

​Agents

​Tools

​Context Keywords

​Best Practices