Alchemy

Registre officiel IA et agents

Serves the Alchemy writing ruleset to any agent, so its prose loses the usual LLM tells.

Installation

Ajoutez ceci à la configuration MCP de votre client (Claude Desktop : claude_desktop_config.json ; Cursor : .cursor/mcp.json ; VS Code et les autres utilisent la même forme « mcpServers »).

NPM package @fernforge/alchemy-mcp
Claude Code
claude mcp add alchemy -- npx -y @fernforge/alchemy-mcp@0.1.1
Configuration JSON (Claude Desktop, Cursor, VS Code)
{
    "mcpServers": {
        "alchemy": {
            "command": "npx",
            "args": [
                "-y",
                "@fernforge/alchemy-mcp@0.1.1"
            ]
        }
    }
}

Documentation

Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.

Sommaire
  1. Alchemy
  2. How do I stop my AI from writing like an LLM?
  3. Before and after
  4. Which LLM tells does it remove?
  5. Use it with Claude, Cursor, or Copilot
  6. Use it as an MCP server
  7. Three ways to install, one ruleset
  8. Where the rules come from
  9. Contributing
  10. License

Alchemy

Alchemy is a drop-in ruleset that stops your AI coding agent from writing like an LLM: no em-dash pile-ups, no "not just X, it's Y", no stray delve. You add it once, your agent reads it before it writes, and the READMEs, commits, and docs it produces start sounding like a person wrote them.

Turn lead into gold. It's one file, about 1000 tokens, that lives next to your agent's other instructions: ALCHEMY.md. Everything else here just gets it into your project.

How do I stop my AI from writing like an LLM?

Install it in your project and point your agent at it. Pick whichever fits your stack:

# Node / npm
npx @fernforge/alchemy init

# Python / pip
pip install alchemy-writing
alchemy init

init writes ALCHEMY.md into your project and links it from whatever agent config you already have: CLAUDE.md, AGENTS.md, .cursorrules, or Copilot instructions. From then on the agent reads the rules as part of its normal context. To print the ruleset to stdout without installing anything:

npx @fernforge/alchemy print   # or: alchemy print

Prefer to do it by hand? Copy ALCHEMY.md into your repo and reference it from your agent's instruction file. That's the whole mechanism. No service, no API, no account.

Before and after

Here's the kind of sentence Alchemy catches. Same fact, two ways of saying it:

Before

Redis isn't just a database — it's a powerful, robust caching layer that unlocks the full potential of your entire stack.

After

Redis is an in-memory store. Put your cache and sessions in it and your database stops being the bottleneck.

The "before" stacks four tells in one sentence: the "isn't just X, it's Y" non-contrast, the adjective pile (powerful, robust), the lone dramatic em-dash, and "unlocks the full potential". None of it says what Redis does. The "after" drops all of it and states one concrete thing you can act on. That's the whole move, applied everywhere the agent writes.

Which LLM tells does it remove?

The concrete ones, by name:

  • Empty contrasts: "not just X, it's Y", "it's not about A, it's about B".
  • Staccato trios and rule-of-three padding: "fast, reliable, scalable", "No X. No Y. Just Z."
  • Stacked adjectives standing in for facts: robust, seamless, powerful, comprehensive.
  • Em-dash pile-ups. The real tell is density, so the rule is: use them rarely.
  • Filler vocabulary: delve, leverage, harness, unlock, elevate, tapestry, realm, showcase.
  • Throat-clearing openers ("In today's fast-paced world", "At its core") and recap closers ("In conclusion", "Ultimately").
  • Restating the prompt before answering it.

The fix is never a synonym swap. It's replacing the vague word with a specific fact: not "robust" but "handles 10k req/sec". The rules push the agent toward the fact.

The principle underneath: no single word proves a machine wrote something. The signal is many of these clustered together over flat, evenly-weighted text. Alchemy targets the clustering, so it thins the tells without stripping a word that's genuinely the right one.

Use it with Claude, Cursor, or Copilot

init detects the config files already in your project and links the ruleset from them, so the same ALCHEMY.md works across agents:

  • Claude Code / Claude reads it via CLAUDE.md.
  • Cursor reads it via .cursorrules.
  • Copilot reads it via its instructions file.
  • Any agent that supports AGENTS.md picks it up there.

One ruleset, whichever agent you're driving.

Use it as an MCP server

To serve the rules on demand across every project instead of committing a file to each repo, run Alchemy as an MCP server. Add it to your client config (Claude Desktop, Cursor, Cline):

{
  "mcpServers": {
    "alchemy": { "command": "npx", "args": ["-y", "@fernforge/alchemy-mcp"] }
  }
}

It exposes a get_writing_rules tool and an alchemy://rules resource, so any MCP-aware agent can pull the ruleset when it's about to write prose. See mcp/ for details.

Three ways to install, one ruleset

All three ship the same rules from the same source, so pick by your toolchain and mix freely:

  • npm: @fernforge/alchemy — npx @fernforge/alchemy init
  • PyPI: alchemy-writing — pip install alchemy-writing
  • MCP: @fernforge/alchemy-mcp — npx @fernforge/alchemy-mcp

Where the rules come from

They're grounded in what people actually flag as AI writing, not guesses: Wikipedia's "Signs of AI writing", the Kobak et al. study measuring which words spiked in research papers after ChatGPT, Pangram's phrase-frequency data, and the long-running arguments on Reddit and in r/Professors about spotting it. It's kept short on purpose: concrete guidance an agent can hold in context, not an essay.

This README follows its own rules. If it reads fine, that's the pitch.

Contributing

Found a tell it misses? Open an issue or a PR with a real before-and-after pair. Concrete examples are worth more than new abstract rules.

Edit the root ALCHEMY.md only. The copies under python/ and mcp/ are generated from it by node scripts/sync-rules.mjs, and CI fails if they drift. The npm, PyPI, and MCP packages publish from GitHub Releases (see .github/workflows).

License

MIT

Questions fréquentes

Qu'est-ce que Alchemy ?

Serves the Alchemy writing ruleset to any agent, so its prose loses the usual LLM tells.

Comment installer Alchemy ?

Il s'exécute sur votre machine. Dans Claude Code : claude mcp add alchemy -- npx -y @fernforge/alchemy-mcp@0.1.1. Pour les autres clients, collez la configuration JSON de cette page dans leurs réglages MCP.

Faut-il une clé API pour Alchemy ?

Son entrée au registre n'indique aucune clé ni secret obligatoire. Certaines fonctions peuvent tout de même demander un compte auprès du service auquel il se connecte.

Alchemy est-il open source ?

Oui. Son code est sur GitHub sous licence MIT.

Qui maintient Alchemy ?

Il est publié par fernforge. AI.tn le référence sans le maintenir ni le recommander.

Issu du registre MCP officiel. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.