Knit Rmd Html

Community

huangwb8

knit-rmd-html

Knit/render R Markdown (.Rmd) to HTML reliably in this repo (auto-bootstrap pandoc, set correct knit_root_dir, and run rmarkdown::render via a Python wrapper).

Overview

Publisher	huangwb8
Repository	`skills`
Skill name	`knit-rmd-html`
Stars	50
Forks	8
Bundled files	3
License	MIT
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
3 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by huangwb8 on GitHub. Read the source before you install it.

Installation

Install the Knit Rmd Html AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/huangwb8/skills/tree/main/skills/beta/knit-rmd-html
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/huangwb8/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/beta/knit-rmd-html .claude/skills/knit-rmd-html

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Knit Rmd Html in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Knit Rmd Html on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Knit Rmd Html is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Knit Rmd → HTML（项目高频场景）

目标

Knit/render R Markdown (.Rmd) to HTML reliably in this repo (auto-bootstrap pandoc, set correct knit_root_dir, and run rmarkdown::render via a Python wrapper).

当用户说"knit 出 html / render Rmd / 生成 HTML 报告"时使用本 skill。

版本由 config.yaml:skill_info.version 统一管理。

流程

输入

输入为待渲染的 .Rmd 路径；可选输入包括项目根目录、输出文件路径、Pandoc 版本/下载选项和 rmarkdown::render 参数。渲染前需确认项目 knit_root_dir、R 和必要模板资源可用。

执行步骤

直接用法

在仓库根目录执行：
- python3 skills/knit-rmd-html/scripts/knit_rmd_html.py <input>.Rmd
- 输出默认写到 <input>.Rmd 同目录：<input>.html

常用参数

指定输出文件：
- python3 skills/knit-rmd-html/scripts/knit_rmd_html.py <input>.Rmd -o <output>.html
指定 pandoc 版本（默认 3.8.3）：
- python3 skills/knit-rmd-html/scripts/knit_rmd_html.py <input>.Rmd --pandoc-version 3.8.3
不自动安装依赖（只做检测；缺什么就报错）：
- python3 skills/knit-rmd-html/scripts/knit_rmd_html.py <input>.Rmd --no-install
静默渲染输出：
- python3 skills/knit-rmd-html/scripts/knit_rmd_html.py <input>.Rmd --quiet

设计要点（为何这样做）

不依赖 R 写脚本：外层用 Python 做编排与环境自检；真正的 knit 仍由 rmarkdown::render() 执行。
自动补齐 pandoc：若系统无 pandoc，自动下载安装到 ~/.local/pandoc/ 并将 ~/.local/bin 放到子进程 PATH 前面。
兼容 Windows ZIP：安全解压后递归寻找唯一的 pandoc / pandoc.exe，兼容根目录与 bin/ 布局并拒绝歧义结果。
输出编码稳定：Rscript 日志始终按 UTF-8 解码并保留真实退出码，不依赖 Windows 控制台 locale。
相对路径更稳：用 knit_root_dir=dirname(input)，确保 Rmd 内 source("xxx.R") 等相对路径在 knit 时仍可用。

工作原理

环境检测：检查 pandoc 和 Rscript 是否在 PATH 中
自动安装：若缺少 pandoc，根据平台自动下载对应版本到 ~/.local/pandoc/
渲染执行：通过 R 的 rmarkdown::render() 执行 knit
输出定位：默认输出到输入文件同目录，可通过 -o 参数指定

输出

成功时在同级目录生成与 Rmd 同名的 HTML，或写入由 -o 指定的输出文件路径；同时保留渲染日志、Pandoc/依赖诊断和任务工作区中的临时产物，不改变输入 Rmd。

输出管理

BenszAPI 任务工作区

校验

校验 Rmd 路径和项目根目录、Pandoc/R 依赖、knit_root_dir 与输出 HTML 存在性；渲染退出码为 0 且 HTML 可读取时才报告成功。

失败与恢复

Pandoc/R 缺失、引导下载失败、路径越界、渲染超时或 rmarkdown::render 返回非零时，保留日志和诊断输出并报告可复现命令；若产生部分输出，由用户按需清理或隔离后再修复依赖/参数重试。

约束

公共硬约束

本块由 docs/templates/skill-common-constraints.md 统一维护；每个 SKILL.md 的 ## 约束 必须逐字同步本块，不得在副本中改写公共规则。

任务需要落盘时，使用唯一的 ./.bensz-api/task-{yyyymmdd-hhmm}-{简短描述}/ 根目录；共享材料放入 shared/，Skill 专属材料放入该 Skill 的 input/、output/、log/。
正式交付物、源代码和正式计划按项目约定保存，不写入任务工作区；未经授权不覆盖、删除、迁移或远程写入。
项目维护变更检查 BAC 可用性并记录需求、AI 产出、工具结果、文件改动和验证摘要；BAC 只做过程审计，不替代署名、责任或合规判断。
不记录 API Key、访问令牌、密码、Cookie、环境/凭据文件、私有 Prompt、身份信息、本地用户名、主机名或不必要的大体积原始数据。
文件路径必须规范化并限制在授权项目范围内；外部 URL、子进程和网络访问遵循最小权限，防止路径遍历、SSRF 和命令注入。
Skill 版本唯一记录在自身 config.yaml:skill_info.version；公开 API、协议、目录或配置变更同步文档与 CHANGELOG.md。
bensz-collect-bugs 是一个 Agent Skill；仅将 Bensz Agent Skill 或 Bensz 基础设施本身的设计缺陷交给它。先脱敏写入 ~/.bensz-skills/bugs/，当前任务不中断，只有用户明确要求才公开上报，禁止直接修改用户已安装的 Skill 源码。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Knit Rmd Html AI skill do?

Knit/render R Markdown (.Rmd) to HTML reliably in this repo (auto-bootstrap pandoc, set correct knit_root_dir, and run rmarkdown::render via a Python wrapper).

Why use Knit Rmd Html on TypingMind?

Because you install it once and use it with any model. Knit Rmd Html is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Knit Rmd Html in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/huangwb8/skills/tree/main/skills/beta/knit-rmd-html. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Knit Rmd Html?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Knit Rmd Html?

As many as you like. As long as a model supports skills, you can use Knit Rmd Html with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Knit Rmd Html AI skill free?

Yes. It is published on GitHub by huangwb8 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Solid

openclaw

OrganizationPopular

Write, port, review, or test Solid 2 UI in OpenClaw (Control UI, plugin views, Canvas hosts), including state ownership, Lit interop during the migration, native overlays, testing, performance, and…

Auto Qa

Run OpenClaw-wide autonomous QA and live/stress campaigns across independent subsystem lanes, with verified fixes and a resumable evidence report.

Autoreview

Structured code review when explicitly requested, preferring OpenAI/Codex before Claude.

Claw Score

Audit or refresh OpenClaw maturity scorecard docs from root taxonomy, maturity scores, and QA evidence artifacts without using maintainer discrawl data or committed inventory reports.

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Knit Rmd → HTML（项目高频场景）

目标

流程

输入

执行步骤

直接用法

常用参数

设计要点（为何这样做）

工作原理

输出

输出管理

BenszAPI 任务工作区

校验

失败与恢复

约束

公共硬约束

Bundled files

Frequently asked questions

Related AI Skills

Set up your own AI workspace now