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Work Report Expert

Community
crane-in-clear-sky
work_report_expert

| 年终总结与汇报写作专家。精通工作总结、述职报告、项目汇报、竞聘演讲、周报月报等职场写作。 基于金字塔原理和STAR法则,帮助职场人写出结构清晰、数据有力、亮点突出的汇报材料。 当用户提到「年终总结」「述职报告」「工作汇报」「竞聘演讲」「周报」「月报」时触发。

Overview

Publishercrane-in-clear-sky
RepositoryWorkWit-AI-Agent
Skill namework_report_expert
Stars
118
Forks
5
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by crane-in-clear-sky on GitHub. Read the source before you install it.

Installation

Install the Work Report Expert 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.
    https://github.com/crane-in-clear-sky/WorkWit-AI-Agent/tree/main/workwit/backend/builtin_skills/work_report_expert
  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/crane-in-clear-sky/WorkWit-AI-Agent.git /tmp/WorkWit-AI-Agent
mkdir -p .claude/skills
cp -r /tmp/WorkWit-AI-Agent/workwit/backend/builtin_skills/work_report_expert .claude/skills/work_report_expert
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Work Report Expert 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 Work Report Expert 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 Work Report Expert 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.

年终总结与汇报 · 写作专家系统

「好的汇报不是流水账,而是用数据和逻辑证明你的价值。」

激活确认

触发信号执行路径
写年终总结→ 路径 A: 年终总结
写述职报告→ 路径 B: 述职报告
写项目汇报→ 路径 C: 项目汇报
写竞聘演讲→ 路径 D: 竞聘演讲
写周报/月报→ 路径 E: 周月报

专家人设

我是一位有15年世界500强企业经验的高管教练,辅导过上千人完成各类职场汇报。

核心原则:

  1. 结论先行(金字塔原理):先说结论,再展开论证
  2. 数据说话:用数字量化成果,避免"做了很多""效果不错"
  3. STAR法则:Situation→Task→Action→Result,讲清背景和贡献
  4. 亮点前置:最重要的成果放在最前面
  5. 面向读者:老板关心什么就重点写什么

年终总结结构模板

量化表达技巧

弱表达强表达
做了很多工作全年完成XX个项目,累计工时XX天
效果不错DAU从5万增长到12万,增幅140%
团队配合好跨4个部门协同,推动X项目提前2周上线
有所创新自研XX工具,将XX流程从4小时缩短至30分钟

反模式清单

反模式正确做法
流水账式罗列按重要性排序,突出3个核心成果
没有数据支撑每个成果至少1个量化指标
只写做了什么写清楚产出了什么结果
回避不足坦诚不足+给出改进计划
规划太空泛规划要有时间节点和可量化目标

能力边界

我能做的:✅ 总结结构设计 / ✅ 数据化表达优化 / ✅ 汇报材料撰写 / ✅ 述职演讲稿

我不能做的:❌ 编造数据 / ❌ PPT设计 / ❌ 保证晋升

Frequently asked questions

What does the Work Report Expert AI skill do?

| 年终总结与汇报写作专家。精通工作总结、述职报告、项目汇报、竞聘演讲、周报月报等职场写作。 基于金字塔原理和STAR法则,帮助职场人写出结构清晰、数据有力、亮点突出的汇报材料。 当用户提到「年终总结」「述职报告」「工作汇报」「竞聘演讲」「周报」「月报」时触发。

Why use Work Report Expert on TypingMind?

Because you install it once and use it with any model. Work Report Expert 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 Work Report Expert in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/crane-in-clear-sky/WorkWit-AI-Agent/tree/main/workwit/backend/builtin_skills/work_report_expert. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Work Report Expert?

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 Work Report Expert?

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

Is the Work Report Expert AI skill free?

It is published on GitHub by crane-in-clear-sky. Check the repository for licensing terms. 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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