Chatting With AWS Devops Agent
AWSOfficialPublished by AWS
- Skill
- Tool integration
- Cloud and DevOps
- Apache-2.0
- No issues found
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill provides a conversational interface to an AWS DevOps Agent, designed for quick, 5-30 second responses regarding cloud infrastructure. It enables users to perform cost optimizations, architecture reviews, topology mapping, and runbook discovery by sending natural language queries. The agent supports context injection, allowing users to include local workspace files like IaC templates or logs to improve the relevance of the analysis. It is intended for lightweight tasks, with clear guidance on when to escalate to deeper incident investigation workflows.
What it does
- Provides a conversational chat interface for AWS infrastructure queries.
- Supports injection of local workspace context like IaC files and logs.
- Facilitates cost optimization and architecture review tasks.
- Enables topology mapping and runbook discovery.
- Manages chat session lifecycles via execution IDs.
- Offers a fallback mechanism to direct AWS API calls if the primary agent is unavailable.
When to use it
- When you need a quick answer about your AWS environment (5-30 seconds).
- When performing cost analysis or architecture reviews.
- When you need to map service topologies or find relevant runbooks.
- When you want to provide local code or configuration context to refine an AWS-related question.
- When you need to perform quick diagnostics on errors or metrics.
Advantages
- Fast, conversational access to complex cloud data.
- Context-aware analysis by combining local files with cloud state.
- Simple session management for follow-up questions.
- Clear escalation path for complex incident investigations.
Usage examples
- “What is causing the 503 errors on the checkout-service?”
- The agent analyzes the provided local context and cloud metrics to identify the root cause of the service errors.
- “Show me the topology for the checkout-stack.”
- The agent returns a mapping of the resources defined in the specified CDK stack.
Install
Download the skill as a ZIP:
https://autogineer.com/agent-skills/aws/chatting-with-aws-devops-agent/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip chatting-with-aws-devops-agent.zip -d .agents/skills
Documentation by AWS
Chat with the AWS DevOps Agent
AgentSpace routing (SigV4 only): If
list_agent_spacesis available in your tool list and the multi-space orchestration skill has NOT been invoked yet this session, invoke it first to determine whichagent_space_idto use. Then passagent_space_idon 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
→ executionIdThen 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-1Tell 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:
Retry the same
chatcall once.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_messagewith theexecution_idfrom thechatresponse.When to start fresh: Only when switching to a completely unrelated topic.
Resuming old chats:
list_chatsreturns previous sessions. Usesend_messagewith an oldexecution_idto 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.
Files
- ATTRIBUTION.mdAdded by AutoGineer946 B
- LICENSELicence file added by AutoGineer9.9 KiB
- NOTICELicence file added by AutoGineer67 B
- SKILL.md5.3 KiB
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Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Needs an MCP server, Needs a command-line tool
Security
No issues found by our static scan· No issues found
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Published by
- AWS
- Publisher
- AWS (Official)
- Source
- aws/agent-toolkit-for-aws · plugins/aws-agents-for-devsecops/skills/chatting-with-aws-devops-agent · commit 0a218f8
- Licence
- Apache License 2.0 (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- NOTICE (added by AutoGineer from NOTICE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by AWS or AWS.
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