PelaPela

Model response tuning for translation work — naturalness, tone, and script guidance, parameterized by language pair. Ships as a Claude Code skill and as an MCP server, so the same tuning methodology works in Claude, ChatGPT (via MCP), and any other MCP-compatible host.

This tunes how a model phrases a translation — word choice, register, script — not the translation engine itself. Point it at whatever model you're already calling.

Why

LLM translations often read as "translated" rather than natural: literal transliteration of ordinary words, mismatched formality, wrong script for the target audience. This package encodes a small, explicit set of rules for catching that, plus a cheap self-check step (fix it yourself before returning, rather than burning a second model call).

Use in Claude Code

Install the plugin, then invoke per language pair with optional tone/script args, in any order:

/pela:en-jp friendly kanaonly
/pela:en-es formal

Supported today: en-jp, en-es. See Adding a pair to extend it.

Use via MCP (ChatGPT and other hosts)

ChatGPT's old Plugins system is deprecated; this ships as an MCP server instead, which ChatGPT and most modern agent hosts support.

npx pelapela-mcp

Or point your MCP host's config at it directly:

{
  "mcpServers": {
    "pelapela": { "command": "npx", "args": ["pelapela-mcp"] }
  }
}

It exposes one prompt and one tool, both named pela_translate_tuning, taking pair (required), tone (optional, default neutral), and script (optional, where the pair supports one).

Hosted / remote MCP (ChatGPT Apps submission, other remote-only hosts)

npx pelapela-mcp above runs over stdio — fine for local hosts (Claude Desktop, most CLI agents), but ChatGPT's app directory and some other hosts require a public HTTPS /mcp endpoint instead. worker/ has that variant, built on Cloudflare Workers + the Agents SDK (McpAgent), same pela_translate_tuning tool, same core/buildTuning.mjs source of truth — just a different transport.

Live: https://pelapela-mcp.jess-901.workers.dev/mcp

cd worker
npm install
npm run dev      # local HTTP test at http://localhost:8788/mcp
npm run deploy   # publish to your own Cloudflare account

Submitting to ChatGPT's app/plugin directory beyond hosting it is a manual, identity-verified process through OpenAI's own submission portal — not something this repo can automate.

Adding a pair

Everything lives in core/buildTuning.mjs — a single PAIR_NOTES entry per pair (naturalness rules, tone notes, script variants where applicable). Add an entry there, add a matching skills/pela-<pair>/SKILL.md following the existing two as a template, and both the Claude skill and the MCP server pick it up automatically (the MCP server reads PAIRS directly from the same module — nothing to duplicate).

Development

npm install
npm test                    # unit tests for the instruction builder
node tests/mcp-smoke.mjs    # real MCP client/server round-trip check

License

MIT