weekly-report

weekly-report is a skill for Claude Code, Codex from yunshu0909/yunshu_skillshub. It costs 51 tokens per session (2,054 once invoked), scanned A, original, MIT.

A weekly-report writing assistant that helps organize the work you did, the value it created, current problems, and next steps.

In plain words
What is it for?
Use it to prepare weekly reports for technical, product, operations, design, testing, sales, or general team work.
Why use it?
It removes the need to turn scattered weekly notes into a clear account of your work. It also helps show context, results, ownership, and boundaries.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Not installable: its command points at a path on the author’s own machine, so it runs nowhere else. The line is /Users/xxx/Documents/周报/.

Good fit Use it to prepare weekly reports for technical, product, operations, design, testing, sales, or general team work.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for weekly-report

README.md
[![agentmods](https://agentmods.dev/badge/skills/yunshu0909/yunshu_skillshub/weekly-report/github.svg)](https://agentmods.dev/skills/yunshu0909/yunshu_skillshub/weekly-report)
Your own site
<a href="https://agentmods.dev/skills/yunshu0909/yunshu_skillshub/weekly-report"><img src="https://agentmods.dev/badge/skills/yunshu0909/yunshu_skillshub/weekly-report/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for weekly-report

Your own site · 80×15
<a href="https://agentmods.dev/skills/yunshu0909/yunshu_skillshub/weekly-report"><img src="https://agentmods.dev/badge/skills/yunshu0909/yunshu_skillshub/weekly-report.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 51 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,054 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00051 $0.02054
Opus 5 $0.00026 $0.01027
Sonnet 5 $0.00010 $0.00411
Haiku 4.5 $0.00005 $0.00205

Measured 12d ago against content hash 61001db99d86, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

weekly-report scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

weekly-report/SKILL.md · 247 lines

How it starts

The opening of the file, as written. The whole thing — 247 lines — stays where its author put it; the contents beside it link to each section on GitHub.

周报写作助手

用途

帮助用户把一周的工作梳理成逻辑清晰、价值明确的周报,让团队了解做了什么、遇到什么问题、下一步计划。

工作流程

第一步:收集素材

引导用户讲述本周工作,可以想到什么说什么,不需要有条理:

  1. 按模块引导:你这周主要做了哪几块的事情?(客户、项目、内部工作等)
  2. 自由描述:每一块具体做了什么?不用组织语言,想到什么说什么
  3. 不打断:让用户先全部讲完,再补充细节

第二步:分类整理

根据用户的工作性质和角色,灵活选择合适的模块分类。以下是不同角色的常见分类参考:

技术/开发角色

  • 功能开发/需求实现
  • Bug修复/问题排查
  • 技术优化/重构
  • Code Review/技术评审
  • 技术调研/学习
  • 文档编写

产品经理角色

  • 需求调研/用户访谈
  • 产品设计/原型设计
  • 需求评审/排期
  • 数据分析/用户反馈
  • 竞品分析
  • 产品迭代/上线

运营角色

  • 活动策划/执行
  • 用户增长/留存
  • 内容运营/社区运营
  • 数据分析/效果复盘
  • 用户反馈处理
  • 渠道合作/商务对接

设计角色

  • UI/视觉设计
  • 交互设计/用户体验
  • 设计规范/组件库
  • 设计评审/走查
  • 视觉优化

测试/QA角色

  • 测试用例编写
  • 功能测试/回归测试
  • 自动化测试
  • Bug跟踪/质量分析
  • 性能测试/安全测试

SA/售前/商务角色

  • 客户跟进/拜访
  • POC/Demo演示
  • 方案设计/技术支持
  • 商务谈判/合同
  • 客户培训/分享

通用模块(适用所有角色):

  • 项目交付/执行
  • 内部提效/工具建设
  • 会议/培训/分享
  • 团队协作/跨部门沟通
  • 学习/调研

使用建议

  • 根据自己的实际工作选择2-4个主要模块
  • 模块名称可以根据自己习惯调整(如"功能开发"可以叫"需求实现")
  • 每个模块下按具体项目/客户/事项进一步细分

第三步:补充关键信息

针对每件事,通过追问补充完整逻辑:

  1. 背景/原因:为什么要做这件事?基于什么需求或问题?
  2. 具体做了什么:采取了什么行动?用了什么方法/工具?
  3. 结果/价值
    • 达到了什么效果?
    • 有具体数字吗?(成本、收益、时间等)
    • 给客户/团队带来了什么价值?
  4. 当前状态
    • 完成了?进行中?等待反馈?
    • 遇到什么卡点或问题?
    • 问题的本质是什么?(技术问题、交付问题、沟通问题?)
  5. 下一步动作
    • 接下来要做什么?
    • 谁来负责?

关键追问模板

  • "这个成本大概是多少?"(能量化的尝试量化)
  • "为什么要做这个?是客户要求还是主动优化?"
  • "结果怎么样?客户反馈如何?"
  • "目前卡在哪里?本质是什么问题?"
  • "下一步谁来处理?"

第四步:讨论调整

给用户看初稿,确认:

  1. 表述习惯:是否保持了用户的表达方式?不要用自己的套路改写
  2. 逻辑完整:每件事是否说清楚了背景→做了什么→结果→下一步?
  3. 重点突出:哪些是重点成果?是否体现出来了?
  4. 问题明确:遇到的卡点和挑战是否说清楚了?

根据用户反馈调整措辞、结构和重点。

第五步:输出文档

生成最终的周报文档,包含:

# 本周工作

## 一、[模块名称]

**1. [客户/项目名称] - [一句话概括]**
[完整描述:背景 → 做了什么 → 结果 → 下一步]

**2. [客户/项目名称] - [一句话概括]**
① [子项1]:[描述]
② [子项2]:[描述]
③ [子项3]:[描述]

**核心卡点/挑战**:[如果有重要问题,单独说明]

## 二、[模块名称]
...

## 下周重点

**1. [重点事项1]**
- [具体内容]

**2. [重点事项2]**
- [具体内容]

核心原则

  1. 用用户的话:保持用户的表达习惯和语气,不要用自己的套路改写
  2. 完整的逻辑链:每件事都要有背景→做了什么→结果→下一步
  3. 能量化的就量化:用户提到数字就写上,用户没说也不强求
  4. 如实展示边界
    • 能搞定的:体现专业能力和价值
    • 搞不定的:说清楚卡在哪、为什么、谁来解决
  5. 明确下一步:每个事项说清楚当前状态和下一步动作
  6. 格式自然:该有的结构要有,但内容要自然成段,不要搞成标签式("做了什么:""取得结果:")

Read the full file on GitHub · 247 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 247 lines · 51 tokens per session scan A 61001db99d86

Subscribe to this mod's changes

weekly-report is a skill published in the GitHub repository yunshu0909/yunshu_skillshub (757 stars, last pushed 1mo ago), licensed MIT. It adds 51 tokens to every session and 2,054 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens

next-partial-prefetching-adoption

Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…

vercel/next.js · 103 tokens