{
  "markdown": "<p align=\"center\">\n  <img src=\"./cover.png\" alt=\"Alchemy — write like a human, not an LLM\" width=\"100%\">\n</p>\n\n# Alchemy\n\nAlchemy 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.\n\nTurn lead into gold. It's one file, about 1000 tokens, that lives next to your agent's other instructions: [`ALCHEMY.md`](./ALCHEMY.md). Everything else here just gets it into your project.\n\n## How do I stop my AI from writing like an LLM?\n\nInstall it in your project and point your agent at it. Pick whichever fits your stack:\n\n```bash\n# Node / npm\nnpx @fernforge/alchemy init\n\n# Python / pip\npip install alchemy-writing\nalchemy init\n```\n\n`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:\n\n```bash\nnpx @fernforge/alchemy print   # or: alchemy print\n```\n\nPrefer to do it by hand? Copy [`ALCHEMY.md`](./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.\n\n## Before and after\n\nHere's the kind of sentence Alchemy catches. Same fact, two ways of saying it:\n\n**Before**\n\n> Redis isn't just a database — it's a powerful, robust caching layer that unlocks the full potential of your entire stack.\n\n**After**\n\n> Redis is an in-memory store. Put your cache and sessions in it and your database stops being the bottleneck.\n\nThe \"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.\n\n## Which LLM tells does it remove?\n\nThe concrete ones, by name:\n\n- Empty contrasts: \"not just X, it's Y\", \"it's not about A, it's about B\".\n- Staccato trios and rule-of-three padding: \"fast, reliable, scalable\", \"No X. No Y. Just Z.\"\n- Stacked adjectives standing in for facts: robust, seamless, powerful, comprehensive.\n- Em-dash pile-ups. The real tell is density, so the rule is: use them rarely.\n- Filler vocabulary: delve, leverage, harness, unlock, elevate, tapestry, realm, showcase.\n- Throat-clearing openers (\"In today's fast-paced world\", \"At its core\") and recap closers (\"In conclusion\", \"Ultimately\").\n- Restating the prompt before answering it.\n\nThe 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.\n\nThe 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.\n\n## Use it with Claude, Cursor, or Copilot\n\n`init` detects the config files already in your project and links the ruleset from them, so the same `ALCHEMY.md` works across agents:\n\n- Claude Code / Claude reads it via `CLAUDE.md`.\n- Cursor reads it via `.cursorrules`.\n- Copilot reads it via its instructions file.\n- Any agent that supports `AGENTS.md` picks it up there.\n\nOne ruleset, whichever agent you're driving.\n\n## Use it as an MCP server\n\nTo 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):\n\n```json\n{\n  \"mcpServers\": {\n    \"alchemy\": { \"command\": \"npx\", \"args\": [\"-y\", \"@fernforge/alchemy-mcp\"] }\n  }\n}\n```\n\nIt 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/`](./mcp) for details.\n\n## Three ways to install, one ruleset\n\nAll three ship the same rules from the same source, so pick by your toolchain and mix freely:\n\n- npm: `@fernforge/alchemy` — `npx @fernforge/alchemy init`\n- PyPI: `alchemy-writing` — `pip install alchemy-writing`\n- MCP: `@fernforge/alchemy-mcp` — `npx @fernforge/alchemy-mcp`\n\n## Where the rules come from\n\nThey'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.\n\nThis README follows its own rules. If it reads fine, that's the pitch.\n\n## Contributing\n\nFound 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.\n\nEdit the root [`ALCHEMY.md`](./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`](./.github/workflows)).\n\n## License\n\nMIT\n",
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