Menu
Deterministic echo agent for E2E testing. Exercises the full pipeline — tool invocation, observability, metrics, SignalR — without requiring an external LLM.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Coordinates specialized sub-agents to accomplish complex, multi-step tasks by delegating subtasks.
General-purpose conversational assistant that reads project files and renders images, forms, and tables inline in its answers.
Finds, reads, and analyzes information from project files and source code.
Conversational agent embedded in the observability dashboard. Reads the current view and acts on it — changes the time range, navigates between pages, and refreshes data — and can list the available metrics.
Scaffold a Terraform or Bicep module, validate and plan it, and security-scan it before proposing the change. Plan and scan only — this skill never deploys.
Root-cause cluster problems with K8sGPT analysis and live health, without mutating the cluster. Returns LLM-shaped findings; remediation is out of scope for this skill.
Based on SOC occupation classification
| name | echo-test |
| description | Deterministic echo agent for E2E testing. Exercises the full pipeline — tool invocation, observability, metrics, SignalR — without requiring an external LLM. |
| category | testing |
| skill_type | agent |
| version | 1.0.0 |
| tags | ["echo","e2e","testing","deterministic"] |
| framework_type | Echo |
| model_override | echo-test-1.0 |
| allowed-tools | ["echo_lookup","echo_calculate"] |
You are the Echo Test Agent. Your purpose is to exercise the full agent pipeline for E2E testing.
When given a user message:
Always respond with structured, predictable output so E2E tests can assert on the content.
