How do I install the Lcp Openai Serve skill?

Run npx skillmds@latest add tomevault-io/lcp-openai-serve in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

What does the Lcp Openai Serve skill do?

Develop apps/openai-serve (Go). Keep OpenAI gateway behavior correct and avoid logging prompts/outputs. Use when this capability is needed. It is listed under Coding & Dev Tools on SkillMD.

Is Lcp Openai Serve safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Lcp Openai Serve?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Lcp Openai Serve free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Lcp Openai Serve?

tomevault-io (@tomevault-io) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Lcp Openai Serve by tomevault-io — Agent Skill

Name: Lcp Openai Serve
Author: tomevault-io

File contents

You are working on the OpenAI-compatible HTTP gateway in apps/openai-serve/.

Scope

Module: apps/openai-serve/
Runtime contract: apps/openai-serve/README.md

Development principles

These are the consolidated rules that previously lived in apps/openai-serve/AGENTS.md:

Design for robustness. Keep modules aligned with SRP.
Use a ubiquitous language. Keep terminology consistent across code and docs.
Test-first. Prefer TDD when changing behavior.
Run golangci-lint v2. When changing code, run make lint and fix findings.
Use cmp.Diff in tests. Compare expected vs actual with github.com/google/go-cmp/cmp.Diff.
Make logging diagnosable. Logging level MUST be configurable (for example via env vars).
Prefer lnd libraries. Use lnd-provided APIs/libraries before re-implementing.

Non-negotiables

Logging is sensitive: do not log raw prompts (messages[].content) or raw model outputs.
Keep behavior stable and explicit: JSON decoding is strict, unsupported fields must be rejected as documented.

Workflow

Read apps/openai-serve/README.md before changing behavior.
When adding config/env vars, document them in apps/openai-serve/README.md and keep defaults sane.
When changing request/response structures, update tests and ensure the documented constraints still hold.

Validation (run from `apps/openai-serve/`)

make test
make lint
make fmt

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Frequently asked questions

Lcp Openai Serve