Alchemy

io.github.fernforge由 GitHub 帳號 fernforge 發布v0.1.1更新於 Nov 10, 2026

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

發布方自己的服務:Alchemy MCP Server

已驗證STDIO僅桌面開發者工具AI 與機器學習

概覽

AI 產生的概覽

提供一套寫作規則,讓 AI 助理在撰寫文件、提交訊息等文字時避開常見的 LLM 腔調。

可以做什麼
Alchemy 提供 get_writing_rules 工具與 alchemy://rules 資源,回傳一份簡短規則集(約 1000 token),列出應避免的 LLM 寫作痕跡:空洞對比、堆砌形容詞、破折號濫用、填充詞與開場套話。助理可在撰寫文字前先讀取規則,讓產出的 README、提交訊息與文件更平實。同一套規則也以檔案形式散布,可從助理的指令檔案中引用。
適用情境
當助理經常在你的專案中撰寫文字,而你希望輸出避開可辨識的 LLM 措辭時,值得加入。若你希望跨專案隨需提供規則,而不是在每個儲存庫中提交規則檔案,也很合適。
執行需求
以 npm 套件 @fernforge/alchemy-mcp 透過 stdio 在本機執行,需要 Node.js 與 npx。未宣告帳號、API 金鑰或環境變數。
安裝前請注意
此伺服器只回傳靜態規則集,不會讀取或修改你的檔案。安裝意味著在本機執行第三方 npm 套件,使用前請先檢視該套件。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Alchemy,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

[Alchemy — write like a human, not an LLM]

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:

bash
# Node / npmnpx @fernforge/alchemy init
# Python / pippip install alchemy-writingalchemy 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:

bash
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):

json
{  "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

來源:README.md,提交 83e5eec

工具

0
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版本歷史

1
  1. v0.1.1最新Sep 16, 2026

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