chatting-with-aws-devops-agent — Claude Code skill
This skill sends AWS infrastructure questions to AWS DevOps Agent for conversational analysis. Use it for cost, architecture, topology, security, and diagnostic questions.
npx skills add aws/agent-toolkit-for-aws --skill chatting-with-aws-devops-agent -a claude-codeWhat chatting-with-aws-devops-agent does
The skill sends a question to AWS DevOps Agent through aws_devops_agent__chat and returns a response in one conversation session. It covers cost analysis, architecture reviews, topology mapping, dependency questions, security audits, runbook discovery, and diagnostics. Local project details such as IaC files, errors, metrics, or deployment data can be included in the message.
For a follow-up, it uses aws_devops_agent__send_message with the execution_id returned by the first call. Previous conversations can be found with aws_devops_agent__list_chats. With SigV4 AgentSpace routing, list_agent_spaces runs first and the selected agent_space_id is sent with later tool calls.
This is not the main path for incident investigation: deeper multi-service work moves to investigating-incidents-with-aws-devops-agent. If the remote MCP server is unavailable, the skill falls back to aws-mcp and AWS CLI commands. Agent responses may contain commands or code, so they require explicit user approval before execution.
What it helps with
- diagnose service errors
- review an AWS architecture
- map resource topology
- find relevant runbooks
- compare configuration options
Example prompts for the agent
- Review the AWS architecture and dependencies for this service.
- Show the topology for
checkout-servicewith its ALB and RDS resources. - Compare costs using these Terraform files and scaling policies.
How to install chatting-with-aws-devops-agent
1Skills CLI (Vercel)
npx skills add aws/agent-toolkit-for-aws --skill chatting-with-aws-devops-agent -a claude-code2Manually: put the files in place
~/.claude/skills/chatting-with-aws-devops-agent/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/chatting-with-aws-devops-agent/
1Skills CLI (Vercel)
npx skills add aws/agent-toolkit-for-aws --skill chatting-with-aws-devops-agent -a codex2Manually: put the files in place
.agents/skills/chatting-with-aws-devops-agent/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add aws/agent-toolkit-for-aws --skill chatting-with-aws-devops-agent -a cursor2Manually: put the files in place
.cursor/skills/chatting-with-aws-devops-agent/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install aws/agent-toolkit-for-aws chatting-with-aws-devops-agent2Manually: put the files in place
.github/skills/chatting-with-aws-devops-agent/SKILL.md1Skills CLI (Vercel)
npx skills add aws/agent-toolkit-for-aws --skill chatting-with-aws-devops-agent -a gemini-cli2Platform CLI
gemini skills install https://github.com/aws/agent-toolkit-for-aws --path plugins/aws-agents-for-devsecops/skills/chatting-with-aws-devops-agentManually: put the files in place
.devin/skills/chatting-with-aws-devops-agent/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add aws/agent-toolkit-for-aws --skill chatting-with-aws-devops-agent -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: How to install skills in Claude Code: five ways
Questions about chatting-with-aws-devops-agent
How do I install chatting-with-aws-devops-agent in Claude Code?
Run npx skills add aws/agent-toolkit-for-aws --skill chatting-with-aws-devops-agent -a claude-code, then run npx skills add aws/agent-toolkit-for-aws --skill chatting-with-aws-devops-agent -a claude-code again. The skill file is at ~/.claude/skills/chatting-with-aws-devops-agent/SKILL.md.
What does chatting-with-aws-devops-agent do?
It opens a short conversational analysis with AWS DevOps Agent for costs, architecture, topology, security, runbooks, and diagnostics. Conversation context stays attached to an execution_id.
How can I continue an AWS DevOps Agent conversation?
Pass the execution_id from the first response to aws_devops_agent__send_message. Use aws_devops_agent__list_chats to browse earlier sessions.
Source text
SKILL.md · Apache-2.0
---
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:
| Phrasing | Response time |
|----------|---------------|
| "Analyze...", "Review...", "Compare...", "What if...", "Show topology..." | 5–30s (chat) |
| "List...", "Show me...", "What is..." | instant (discovery) |
| "Investigate...", "Root cause of...", "What's wrong with..." | 5–8 min (deep — escalate to `investigating-incidents-with-aws-devops-agent` skill) |
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:
```bash
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.
© aws · Apache-2.0 · aws/agent-toolkit-for-aws