# Skippy Server

> Skippy Server is an Agent Skill for devops & security published in the Mesh-LLM/mesh-llm repository on GitHub: a SKILL.md instruction file an AI agent can load to do this task.

Use this skill when running, configuring, debugging, or embedding skippy-server, binary stage transport, OpenAI frontend integration, activation wire dtype settings, stage configs, lifecycle status, or nonblocking telemetry.

- Skill name: `skippy-server`
- Category: [DevOps & Security](https://www.openparable.com/skill/devops-security/1)
- Source: https://github.com/Mesh-LLM/mesh-llm/blob/HEAD/.agents/skills/skippy-server/SKILL.md
- Repository: Mesh-LLM/mesh-llm (2,502 GitHub stars when collected)

## SKILL.md

# skippy-server

Use this skill for skippy serving, embedded runtime lifecycle, and binary
stage-to-stage transport.

## Current Repo Shape

The mesh integration embeds `skippy-server` through Rust APIs instead of
launching it as mesh's public OpenAI surface. Public OpenAI compatibility
belongs in `openai-frontend`; `skippy-server` should remain the backend stage
runtime.

Important crates:

```text
crates/skippy-server
crates/skippy-protocol
crates/skippy-runtime
crates/mesh-llm/src/inference/skippy
```

## Validation

Run cargo commands serially:

```bash
cargo check -p mesh-llm
cargo test -p skippy-server --lib
cargo test -p skippy-protocol --lib
cargo test -p mesh-llm-host-runtime --lib inference::skippy
```

For lifecycle/status changes, also run:

```bash
cargo test -p mesh-llm-host-runtime --lib
```

## Rules

Do not reintroduce standalone `kv-server` or `ngram-pool` dependencies into
mesh. Keep structured outputs, tools, logprobs, and `/v1/responses`
compatibility in `openai-frontend`.

Stage status exposed by mesh should be backend-neutral at the API boundary.
Backend-specific details can remain in internal skippy structs.

---

Source: https://www.openparable.com/skill/devops-security/skippy-server (OpenParable). Cite the canonical URL above.