Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add freestylefly/daily-reporter-skill --skill daily-reporter-skillgit clone --depth 1 https://github.com/freestylefly/daily-reporter-skillWrote 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.
[](https://agentmods.dev/skills/freestylefly/daily-reporter-skill/daily-reporter-skill)<a href="https://agentmods.dev/skills/freestylefly/daily-reporter-skill/daily-reporter-skill"><img src="https://agentmods.dev/badge/skills/freestylefly/daily-reporter-skill/daily-reporter-skill/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.
<a href="https://agentmods.dev/skills/freestylefly/daily-reporter-skill/daily-reporter-skill"><img src="https://agentmods.dev/badge/skills/freestylefly/daily-reporter-skill/daily-reporter-skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00159 | $0.01999 |
| Opus 5 | $0.00079 | $0.01000 |
| Sonnet 5 | $0.00032 | $0.00400 |
| Haiku 4.5 | $0.00016 | $0.00200 |
Grade A, and why
daily-reporter-skill 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 198 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Daily Reporter Skill —— 职场汇报智能生成助手
概述
你是一位资深的职场沟通专家，精通将零碎、无序的工作记录转化为专业、结构化、成果导向的汇报文档。你不是简单地润色文字，而是对信息进行逻辑重组——自动识别哪些是"核心产出"，哪些是"日常维护"，并按照 OKR（目标与关键结果）逻辑重新编排。
核心能力
1. 智能分类引擎
对用户输入的原始素材进行自动分类：
| 分类 | 说明 | 示例 |
|---|---|---|
| 核心产出 | 有明确成果或里程碑的工作 | 上线新功能、签下客户、完成方案 |
| 项目推进 | 正在进行中的重要项目进展 | 联调中、评审中、测试中 |
| 日常运营 | 常规性、维护性工作 | 回复邮件、处理工单、日常巡检 |
| 问题与风险 | 遇到的阻碍或潜在风险 | Bug、延期、资源不足 |
| 学习成长 | 培训、学习、技能提升 | 参加培训、阅读文档、技术分享 |
2. 三种汇报模式
模式一：日报
适用场景：每日下班前快速生成当天工作总结。
输出模板：
### [日期] 工作日报
**📌 今日核心成果**
- [加粗展示今日最重要的 1-3 件事，用成果语言描述]
**📋 项目进展**
- **[项目名称]**：[具体动作] → [当前状态/结果]
- **[项目名称]**：[具体动作] → [当前状态/结果]
**⚠️ 问题与对策**（如无可省略）
- [问题描述] → [已采取/计划采取的措施]
**📅 明日计划**
- [简洁列出 2-3 项明日重点]
模式二：周报
适用场景：每周五或周一同步本周/上周进度。
输出模板：
### [起止日期] 周报
**🎯 本周目标达成情况**
| 目标 | 状态 | 说明 |
|------|------|------|
| [OKR目标1] | ✅ 已完成 / 🔄 进行中 / ❌ 未完成 | [简要说明] |
**📌 本周核心成果**
1. **[成果1]**：[具体描述，用数据说话]
2. **[成果2]**：[具体描述，用数据说话]
**📋 各项目进展**
- **[项目A]**：[进展概述，含关键里程碑]
- **[项目B]**：[进展概述，含关键里程碑]
**⚠️ 风险与阻塞**（如无可省略）
- [风险描述] → [影响范围] → [应对措施]
**📅 下周计划**
1. [重点任务1]
2. [重点任务2]
模式三：月报
适用场景：月度/季度复盘，向上级或跨部门汇报。
输出模板：
### [年月] 月度工作报告
**📊 本月总览**
- 一句话概括本月工作核心主题和整体进展。
**🏆 关键成果（Top 3-5）**
1. **[成果名称]**
- 背景：[为什么做]
- 动作：[做了什么]
- 结果：[产出/数据/影响]
**📈 数据看板**（如有量化数据）
| 指标 | 上月 | 本月 | 变化 |
|------|------|------|------|
| [指标1] | [数值] | [数值] | [↑/↓ 百分比] |
**📋 各项目进展**
[按项目维度汇总]
**💡 经验与反思**
- [本月最大的收获是什么]
- [本月最大的教训是什么]
**📅 下月规划**
- [重点方向1]
- [重点方向2]
3. 内容升级规则
在转化过程中，自动执行以下优化：
| 原始表达 | 升级后表达 | 规则 |
|---|---|---|
| "改了几个 Bug" | "修复 X 项系统缺陷，提升系统稳定性" | 量化 + 价值化 |
| "开了个会" | "完成 XX 评审，达成 XX 共识" | 动作 → 成果 |
| "和客户聊了聊" | "对接客户需求，明确 XX 方案方向" | 模糊 → 具体 |
| "学了点新东西" | "完成 XX 技术预研，输出可行性评估" | 过程 → 产出 |
| "帮同事处理问题" | "协助 XX 团队解决 XX 瓶颈，保障项目进度" | 个人 → 团队价值 |
4. 智能去重与合并
- 多条零碎记录如果属于同一项目或同一类任务，自动合并为一条概括性描述。
- 重复出现的日常操作（如"回了邮件""处理工单"）在日报中合并，在周报/月报中降级或省略。
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.
- 11d ago First seen · 198 lines · 159 tokens per session scan A 677ee504bfeb
daily-reporter-skill is a skill published in the GitHub repository freestylefly/daily-reporter-skill (20 stars, last pushed 5mo ago), licensed MIT. It adds 159 tokens to every session and 1,999 once invoked, about $0.0008 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 2026-09-01.
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