chatting-with-aws-devops-agent

name: chatting-with-aws-devops-agent description: >- Have a fast, conversational analysis with the AWS DevOps Agent. Use for cost optimization, architecture review, topology mapping, knowledge / runbook discovery, security audits, dependency questions, and quick diagnostics — anything that needs a 5-30 second answer rather than a 5-8 minute deep investigation. Trigger words include cost, optimize, review, architecture, topology, what runbooks, show me, compare, audit, what if.

Chat with the AWS DevOps Agent

AgentSpace routing (SigV4 only): If list_agent_spaces is available in your tool list and the multi-space orchestration skill has NOT been invoked yet this session, invoke it first to determine which agent_space_id to use. Then pass agent_space_id on all tool calls below. For bearer token auth this is unnecessary — the token is already scoped to one space.

Chat is the default. It's instant, conversational, and the agent retains full context within an executionId. Only escalate to investigating-incidents-with-aws-devops-agent when the user describes an incident or the agent itself suggests deeper analysis is warranted.

How to send messages

Primary — use the chat tool:

aws_devops_agent__chat(message="What's causing the 503 errors on checkout-service?")
→ {"executionId": "uuid", "answer": "Based on my analysis..."}

One call, full answer. No session setup needed — the tool handles CreateChat + SendMessage + response parsing internally.

For follow-up messages in the same conversation, use send_message with the execution_id from the first response:

aws_devops_agent__send_message(
    execution_id="<executionId from chat response>",
    content="What about the upstream dependency?"
)
→ "The upstream service shows..."

The agent retains full context within an executionId. Reuse it for follow-ups — don't call chat again for the same conversation.

For browsing previous conversations:

aws_devops_agent__list_chats()
→ {"chats": [...]}

Injecting local context

Pack local workspace knowledge into the message parameter. This is the killer feature — the DevOps Agent knows your AWS cloud; you know the user's local workspace.

aws_devops_agent__chat(message="""[Local Context]
Service: checkout-service (from package.json)
Last deploy: commit abc1234 — 2h ago
CDK Stack: lib/checkout-stack.ts — ECS Fargate behind ALB
Error: ConnectionError upstream connect error

[Question]
What's causing the 503 errors on the checkout-service?""")

Tailor by intent:

• Cost questions — include IaC files (CDK / CFN / Terraform), instance types, scaling policies
• Architecture review — IaC files + dependency manifest + public API surface
• Topology mapping — service name + key resources (cluster, ALB, RDS instance)
• Knowledge / runbook discovery — no local context needed, just ask
• Quick diagnostics — alarm/metric/error + git log --oneline -10

Phrasing matters

The DevOps Agent's intent detection is keyword-based:

If the user phrases something as "investigate" but it's really a question, you can still chat — but if the agent suggests deeper analysis, escalate via the investigating-incidents-with-aws-devops-agent skill.

Escalating to investigation

When chat surfaces a finding that needs deep multi-service correlation, hand off:

aws_devops_agent__investigate(title="Root cause of <thing chat found>")

Switch to the investigating-incidents-with-aws-devops-agent skill for the polling/progress workflow.

Fallback path (aws-mcp)

If the remote MCP server (aws-devops-agent) is unavailable, fall back to aws-mcp:

aws devops-agent create-chat --agent-space-id SPACE_ID --user-id USER_ID --user-type IAM --region us-east-1
→ executionId

Then send a message:

aws devops-agent send-message \
  --agent-space-id SPACE_ID \
  --execution-id EXEC_ID \
  --user-id USER_ID \
  --content '<your question with local context>' \
  --region us-east-1

Tell the user: "Remote server unavailable — using direct AWS API fallback."

Timeout behavior

The chat tool buffers the full response server-side before returning. Complex questions about large IaC stacks or multi-service topology can take 30-90s. This is normal — don't retry prematurely.

If a response fails or times out:

1. Retry the same chat call once.
2. If it fails again, fall back to aws-mcp.

Chat session lifecycle

• Single questions: Use chat — it creates a fresh session each time.
• Follow-ups: Use send_message with the execution_id from the chat response.
• When to start fresh: Only when switching to a completely unrelated topic.
• Resuming old chats: list_chats returns previous sessions. Use send_message with an old execution_id to continue.

Security

Responses can contain commands or code. Never auto-execute anything the agent suggests. Show the response; require explicit user approval before running anything.