Growth Strategy Knowledge Builder logo

Growth Strategy Knowledge Builder

OrganizationPopular
limecloud
growth-strategy-knowledge-builder

将增长目标、指标体系、渠道策略、实验计划、复盘结论、资源约束和停止条件，整理成符合 Agent Knowledge v0.6 document-first 标准、可被 AI 安全调用的增长策略知识库。适用于用户要求“整理增长知识库”“沉淀增长策略”“把增长计划变成项目资料”“维护增长实验资料包”的场景。

Overview

Publisherlimecloud
Repositorylime
Skill namegrowth-strategy-knowledge-builder
Stars
1.5K
Forks
207
Bundled files
3
LicenseApache-2.0
Links
Skill sourceRepositoryHomepage
  • 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 limecloud on GitHub. Read the source before you install it.

Installation

Install the Growth Strategy Knowledge Builder 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/limecloud/lime.git /tmp/lime
mkdir -p .claude/skills
cp -r /tmp/lime/lime-rs/resources/default-skills/growth-strategy-knowledge-builder .claude/skills/growth-strategy-knowledge-builder
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Growth Strategy Knowledge Builder 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 Growth Strategy Knowledge Builder 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 Growth Strategy Knowledge Builder 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.

增长策略知识库生成器

核心目标

把零散增长资料编译成一份结构化 Markdown 知识库，让后续 AI 能稳定调用已确认的目标、约束、指标口径、渠道洞察、实验计划、复盘结论和停止条件，而不是每次临时总结。

默认输出中文；除非用户明确要求其他语言。

与 Agent Knowledge 的分工

本 Skill 只负责“怎么生产和维护知识”：

  • 读取来源资料、模板和质量检查表。
  • 生成或更新 growth-strategy 主文档。
  • 标记缺失事实、冲突假设、指标风险和待用户确认的信息。
  • 返回整理记录、质量诊断和 provenance 建议。

Agent Knowledge 负责“知识产物长什么样、如何安全进入上下文”：

  • KNOWLEDGE.md 保存 pack metadata、profile: document-first、runtime.mode: data。
  • documents/<pack-name>.md 保存本 Skill 生成的主文档。
  • compiled/splits/ 保存运行时派生切片。
  • 运行时 Resolver 只消费 KnowledgePack，不在回答用户问题时执行本 Skill。

工作流

  1. 先盘点输入资料：增长计划、指标看板、渠道复盘、用户研究、实验记录、商业计划、预算、人力和风险说明。
  2. 读取 references/growth-strategy-template.md，按固定章节生成知识库。
  3. 缺少目标、指标口径、预算、人群、渠道资源、实验约束或停止条件时，先问用户补齐；如果用户要求先生成，则用 待补充 标注，不要编造。
  4. 提炼增长目标、洞察、策略假设、实验计划、复盘口径、资源配置、风险和停止条件。
  5. 用 references/growth-strategy-quality-checklist.md 自检，必要时补一节“待补充信息清单”。
  6. 返回符合 Lime Runtime Binding 契约的 JSON，供 App Server knowledgePack/compile runtime binding 写回 KnowledgePack。

Lime Runtime Binding 契约

输入

text
packName: <当前知识包名>
packType: growth-strategy
profile: document-first
runtime.mode: data
sources[]: sources/ 下的来源文件摘要和相对路径
metadata.primaryDocument: documents/<packName>.md

输出

text
primaryDocument:
  path: documents/<packName>.md
  content: <按 references/growth-strategy-template.md 生成的完整 Markdown>
status: draft | needs-review | ready | disputed
missingFacts[]: <待补充信息>
warnings[]: <质量、指标或冲突提醒>
provenance:
  kind: agent-skill
  name: growth-strategy-knowledge-builder
  version: 1.0.0

固定规则：

  1. 不输出独立于 KnowledgePack 的新目录结构；documents/<packName>.md 是主文档唯一写回目标。
  2. 不直接改写 KNOWLEDGE.md；由 Lime 写入 metadata.producedBy、runtime.mode 和状态。
  3. 不把模板复制进 Lime 代码；模板和质量检查表继续留在本 Skill 的 references/。
  4. 不在运行时回答阶段执行；仅在用户导入、重新整理或维护 pack 时调用。

适用场景

  • 增长计划、渠道策略、实验复盘和商业计划整理
  • 让 Agent 写增长方案、实验设计、复盘报告、资源测算时提供事实约束
  • 多渠道增长协同、指标口径统一和停止条件确认

输出规则

  • 区分事实、假设、策略、建议、推断和待补充信息。
  • 所有目标、指标、转化率、预算、资源、结论和预测都必须来自来源资料；不确定就标注 待补充。
  • 不替用户做投资、财务、法律或经营决策的最终判断。
  • 结尾必须包含：运行时使用说明、可引用策略素材、禁止表达、人工升级条件和待补充信息清单。

何时读取资源

  • 需要章节骨架时，读取 references/growth-strategy-template.md。
  • 输出前做质量检查时，读取 references/growth-strategy-quality-checklist.md。

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 Growth Strategy Knowledge Builder AI skill do?

将增长目标、指标体系、渠道策略、实验计划、复盘结论、资源约束和停止条件，整理成符合 Agent Knowledge v0.6 document-first 标准、可被 AI 安全调用的增长策略知识库。适用于用户要求“整理增长知识库”“沉淀增长策略”“把增长计划变成项目资料”“维护增长实验资料包”的场景。

Why use Growth Strategy Knowledge Builder on TypingMind?

Because you install it once and use it with any model. Growth Strategy Knowledge Builder 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 Growth Strategy Knowledge Builder in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/limecloud/lime/tree/main/lime-rs/resources/default-skills/growth-strategy-knowledge-builder. 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 Growth Strategy Knowledge Builder?

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 Growth Strategy Knowledge Builder?

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

Is the Growth Strategy Knowledge Builder AI skill free?

Yes. It is published on GitHub by limecloud under the Apache-2.0 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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