A
Anonyfox/lfm
Agent-first landing page compiler: one Go binary plus skills that make Claude Code, Codex or Cursor research…
SECURITY.md ✓
在 GitHub 查看 ↗链接已于 2026-11-12 核查 · HTTP 200 · 打开的是厂商自己的官网
安装与配置
取自该仓库的安装命令
go install github.com/Anonyfox/lfm/cmd/lfm@latest
解析自我们于 2026-10-26 抓取的该仓库 README;我们未执行过。
这条是仓库自己写的安装方式,不是 MCP 客户端配置,所以不生成 JSON。
配置项的键名以你的客户端为准:客户端与 CLI
- ★ 数取值
- 1 ★ · Anonyfox/lfm · 取自 GitHub 搜索 API · (2026-11-13 20:00:50 核对)
- 来源明细
- 从该仓库的 GitHub 页面直接读取 · 条目类型:开源项目
- 收录与活跃
- 收录于 2026-10-23 · 最近见到 2026-11-14 · 共见到 26 次 · 被 2 个来源列出
- 评分构成
- 综合分 203 · 1 ★ · 2 个来源 · repo
- 安装
go install github.com/Anonyfox/lfm/cmd/lfm@latest
常见问题(答案都来自我们的记录)
怎么安装?
该仓库给出的安装命令是
go install github.com/Anonyfox/lfm/cmd/lfm@latest。我们的记录里它是仓库自己提供的;不保证在你的客户端上直接可用。它适合谁 / 用来做什么?
我们把它归在这些标签下: Agent 技能。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
仓库
Anonyfox/lfm;我们收录于 2026-10-23;最近见到 2026-11-14。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。# lfm
以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →
Sell before you build: one binary and a skill that make your coding agent research real buyers and
ship one checked, fast landing page with a payment link.
sh
curl -fsSL https://lfm.cash/install.sh | sh
lfm is an agent-first page compiler. Your coding agent researches real buyers, writes a design
concept from what they say, and builds one HTML template with its config and assets. lfm compiles that into a
standalone static folder and refuses to ship a page that is broken, slow, inaccessible, invisible to
search or full of generic AI design defaults. Every finding says how to fix it.
No framework, no platform, no runtime: one binary, one page, one folder you upload anywhere. No MCP
server either: a CLI with --json plus one SKILL.md is the whole agent interface.
## Ask your agent
Give any coding agent (Claude Code, Codex, Cursor, OpenCode, Gemini CLI and others) this request:
> Make a landing page for my sourdough course with lfm: https://lfm.cash/SKILL.md
SKILL.md tells the agent how to install lfm, set up a project and follow the process.
To have every agent session pick it up by itself for requests like "generate me a landing page", install
it once as a user skill:
sh
for d in ~/.agents/skills/lfm ~/.claude/skills/lfm; do mkdir -p "$d" && curl -fsSL https://lfm.cash/SKILL.md -o "$d/SKILL.md"; done
~/.agents/skills is read by Codex, Cursor, OpenCode, Gemini CLI and GitHub Copilot; ~/.claude/skills
by Claude Code. Keep only the one your agents need.
On Grok Bot, add the lfm.cash bot: it installs lfm on its own computer and runs the same
process, asking you only what you decide. Its setup is in docs/grok-bot.md.
## Install
The script at the top downloads the release for macOS or Linux (amd64
or arm64), checks it against the release checksums and puts lfm in ~/.local/bin, without sudo.
LFMVERSION=v0.0.2 pins a release and LFMINSTALLDIR changes the folder. With Homebrew:
sh
brew install anonyfox/tap/lfm
With Go 1.26 or newer:
sh
go install github.com/Anonyfox/lfm/cmd/lfm@latest
Optional: Chrome or Chromium for lfm compile --release, and Lighthouse for its scores. Missing tools
are reported and skipped, never installed.
## Start a page
sh
lfm init sourdough-course # a starter project that compiles cleanly
cd sourdough-course
lfm skills install # the process skills, where your agent loads them
lfm compile # findings, output/ and the next step
Then ask your agent for the page. It works in three phases, each with its own skill:
1. research: real buyer voices and competitor pages, verbatim and dated, into research/.
2. design: concept.md from the research: buyer, mechanism, direction, palette, type, imagery,
motion and copy, every decision cited to a source.
3. implementation: the page from concept.md, until lfm compile --release is clean and every
saved frame holds up on phone and desktop.
The compiler checks each handover: missing research, an uncited concept or a page that ignores the
concept's palette, type and imagery show up as findings. Every report ends with the next step, such as
Next (design): write concept.md from the research., and names the skill for it, so an agent working
unattended stays on the path. When it says deploy, upload output/ to the URL in lfm.json.
ship one checked, fast landing page with a payment link.
sh
curl -fsSL https://lfm.cash/install.sh | sh
lfm is an agent-first page compiler. Your coding agent researches real buyers, writes a design
concept from what they say, and builds one HTML template with its config and assets. lfm compiles that into a
standalone static folder and refuses to ship a page that is broken, slow, inaccessible, invisible to
search or full of generic AI design defaults. Every finding says how to fix it.
No framework, no platform, no runtime: one binary, one page, one folder you upload anywhere. No MCP
server either: a CLI with --json plus one SKILL.md is the whole agent interface.
## Ask your agent
Give any coding agent (Claude Code, Codex, Cursor, OpenCode, Gemini CLI and others) this request:
> Make a landing page for my sourdough course with lfm: https://lfm.cash/SKILL.md
SKILL.md tells the agent how to install lfm, set up a project and follow the process.
To have every agent session pick it up by itself for requests like "generate me a landing page", install
it once as a user skill:
sh
for d in ~/.agents/skills/lfm ~/.claude/skills/lfm; do mkdir -p "$d" && curl -fsSL https://lfm.cash/SKILL.md -o "$d/SKILL.md"; done
~/.agents/skills is read by Codex, Cursor, OpenCode, Gemini CLI and GitHub Copilot; ~/.claude/skills
by Claude Code. Keep only the one your agents need.
On Grok Bot, add the lfm.cash bot: it installs lfm on its own computer and runs the same
process, asking you only what you decide. Its setup is in docs/grok-bot.md.
## Install
The script at the top downloads the release for macOS or Linux (amd64
or arm64), checks it against the release checksums and puts lfm in ~/.local/bin, without sudo.
LFMVERSION=v0.0.2 pins a release and LFMINSTALLDIR changes the folder. With Homebrew:
sh
brew install anonyfox/tap/lfm
With Go 1.26 or newer:
sh
go install github.com/Anonyfox/lfm/cmd/lfm@latest
Optional: Chrome or Chromium for lfm compile --release, and Lighthouse for its scores. Missing tools
are reported and skipped, never installed.
## Start a page
sh
lfm init sourdough-course # a starter project that compiles cleanly
cd sourdough-course
lfm skills install # the process skills, where your agent loads them
lfm compile # findings, output/ and the next step
Then ask your agent for the page. It works in three phases, each with its own skill:
1. research: real buyer voices and competitor pages, verbatim and dated, into research/.
2. design: concept.md from the research: buyer, mechanism, direction, palette, type, imagery,
motion and copy, every decision cited to a source.
3. implementation: the page from concept.md, until lfm compile --release is clean and every
saved frame holds up on phone and desktop.
The compiler checks each handover: missing research, an uncited concept or a page that ignores the
concept's palette, type and imagery show up as findings. Every report ends with the next step, such as
Next (design): write concept.md from the research., and names the skill for it, so an agent working
unattended stays on the path. When it says deploy, upload output/ to the URL in lfm.json.
收录徽章(可选)
想把收录标记放进 README 就复制这行,可选,不影响收录。
[](https://anclum.com/zh/s/anonyfox-lfm/)
- 来源
- github · https://github.com/Anonyfox/lfm
- 按领域浏览
- Agent 技能
- Traction
- 1 ★
- 收录来源
- 2 个独立来源
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SECURITY.md(我们只核文件存在,未核内容)
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