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Hello Hermes

AI Agent Updated 2026.08.30

Paste the following prompt into your AI chat to install this skill:

Please follow https://skillhub.cn/install/skillhub.md to install @user_e634750a/hello-hermes-user-e634750a.

About this skill

Problem

Hello Hermes is a minimal smoke-test skill for validating an Agent Skills publication loop: whether a skill can be created automatically, exposed through SKILL.md, and later used to steer a model toward structured output. It is not a business skill; the point is to exercise the basic cycle of publication instructions, stepwise field collection, and JSON emission. It is especially useful for end-to-end checks across a publishing platform, a model gateway, and a skill loader.

How It Works

According to the materials, it is the first Skill published automatically through Hermes Agent. Its runtime behavior is intentionally narrow:
- The skill instructions ask the model to request fields step by step.
- The model collects user-provided values in the requested order.
- The final response merges those values into a JSON object rather than free-form prose.

This makes it useful as a template or regression example: first confirm that the skill loads correctly, then check whether the model follows the structured-output constraint.

Boundaries

It covers only a minimal example. Do not treat it as a full Agent capability. If the task requires real business rules, multi-step tool calls, permission checks, or external system access, the SKILL.md needs to be extended with the corresponding tools, validation, and execution policies.

Use Cases

  • Validate a minimal Hermes Agent-published skill loads and exposes its SKILL.md in a skill platform smoke test.
  • Collect user-provided fields step by step in a new chat and return the final result as one JSON object.
  • Check whether the model follows the skill's stepwise prompting constraint during gateway regression tests.
  • Trace a publishing pipeline to confirm metadata, canonical name, and SKILL.md instructions reach the downstream model.

Best For

  • Skill platform engineers who need a pre-release check that a minimal skill loads and returns structured JSON.
  • Agent gateway testers who need to verify that a downstream model follows SKILL.md field-collection steps.
  • Platform SREs who need to trace skill metadata, canonical names, and publication flow to execution.
  • Developer-experience teams who need a tiny sample to confirm a new publishing channel preserves skill instructions.