Claude-skill-registry libllm

install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/libllm" ~/.claude/skills/majiayu000-claude-skill-registry-libllm && rm -rf "$T"
manifest: skills/data/libllm/SKILL.md
source content

libllm Skill

When to Use

  • Making chat completion requests to LLM providers
  • Generating text embeddings for vector search
  • Integrating with OpenAI-compatible APIs
  • Handling streaming LLM responses

Key Concepts

LlmApi: HTTP client for OpenAI-compatible endpoints. Handles authentication, streaming, and response parsing.

DEFAULT_MAX_TOKENS: Standard token limit for completions.

Usage Patterns

Pattern 1: Chat completion

import { LlmApi } from "@copilot-ld/libllm";

const api = new LlmApi(config, logger);
const response = await api.completion([{ role: "user", content: "Hello" }], {
  model: "gpt-4",
  maxTokens: 1000,
});

Pattern 2: Generate embeddings

const embeddings = await api.embed(["text to embed"]);
// Returns array of vectors

Integration

Used by LLM service. Configurable via environment for different providers (OpenAI, Azure, GitHub Models).