Individual skill
chatting-with-aws-devops-agent
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.
plugins/aws-agents-for-devsecops/skills/chatting-with-aws-devops-agent/SKILL.md
Source commit 1761e96813ebcbd43ed81d19e837219033f0afe5
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- Yes
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Network or broad shell
- Last checked
- Nov 9, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
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Repository context
- Repository stars (not skill ratings)
- 3,440
- Repository last updated
- Nov 8, 2026
- License
- Apache-2.0
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- security Derived category
- engineering Derived category
- devops Derived category
Files and excerpt
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# 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..."}
```