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Lov Distill To System

Organization
lovstudio
lov-distill-to-system

把有证据的可复用经验写入最合适的项目或共享 Agent 规范。支持明确输入与结果回读。Use to persist a reusable lesson in agent instructions.

Overview

Publisherlovstudio
Repositoryskills
Skill namelov-distill-to-system
Stars
67
Forks
17
Bundled files
10
LicenseMIT
Links
  • 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.

  • 10 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by lovstudio on GitHub. Read the source before you install it.

Installation

Install the Lov Distill To System AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. 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.
2

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/lovstudio/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/distill-to-system .claude/skills/lov-distill-to-system
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Lov Distill To System 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 Lov Distill To System 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 Lov Distill To System 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.

经验入规 · Lessons to Rules

把有证据的可复用经验写入最合适的项目或共享 Agent 规范。

Triggers

Activate when

  • “把有证据的可复用经验写入最合适的项目或共享 Agent 规范。”
  • “Persist a reusable lesson in agent instructions.”

Do not activate when

  • 只是查询本 Skill 的说明,或请求与上述结果无关的任务;不执行实际业务操作。
  • 用户仅要预览或审查时,不进入修改、提交或发布分支。

Execution boundary

自然语言请求即可触发;无需旧 slash 路径、参数插值或指定助手。明确解析当前请求中的 项目、目标文件、选项与输出位置;用当前宿主实际提供的文件、搜索、CLI 和浏览器能力。 项目依赖版本与外部 API 在执行时核实,不能假设示例是现行配置。随包脚本从 Skill 根解析, 业务文件从目标项目根解析。先读当前状态,保护已有未提交内容与其他任务的暂存区。 分析、预览请求保持只读;修改、提交、推送、部署和发布各依当前请求的明确范围执行。 不绕过保护、自动发送消息、强制结束用户进程或抢前台。失败保留可诊断原始错误。

Workflow

  1. 解析待保存经验及适用范围,先定位当前项目规范、领域 reference 或目标 Skill,避免把局部问题扩大为全局规则。

  2. 读取目标并检查重复、冲突和优先级;对时效性的 API 或工具事实先查证,保留来源与生效时间。

  3. 将触发条件、正确动作、边界写成一到三行可执行规则,放在最窄 canonical 层。直接用户要求保存才持久化,推断仅作为建议。

  4. 保留编号、链接和版本约定,按项目要求更新 CHANGELOG 并验证宿主链接。禁止硬编码作者主目录、密钥和未经核实的弃用日期。

  5. 回读新增规则并报告确切目标;不把本地规范修改自动发布到远程。

Composition

执行前读取 能力组合,按明确制品交接相邻能力。

Runtime context (shared)

运行前读取本包 skill.yamlProfile 合同。优先级为当前请求、 项目上下文、本 Skill records、共享 preferences、brand/user Profile、安全默认值。 只读取声明字段;没有专用运行时的宿主可使用 scripts/profile_store.py 读取共享 Profile。 配置缺失只问影响结果的一个问题。用户明确要求长期保存的值通过该脚本原子写入, 报告实际路径;不保存推断、凭据或其他任务的资料。

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 Lov Distill To System AI skill do?

把有证据的可复用经验写入最合适的项目或共享 Agent 规范。支持明确输入与结果回读。Use to persist a reusable lesson in agent instructions.

Why use Lov Distill To System on TypingMind?

Because you install it once and use it with any model. Lov Distill To System 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 Lov Distill To System in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/lovstudio/skills/tree/main/skills/distill-to-system. 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 Lov Distill To System?

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 Lov Distill To System?

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

Is the Lov Distill To System AI skill free?

Yes. It is published on GitHub by lovstudio 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.

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