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 LingyiChen-AI/OpenSkills --skill weekly-report-to-annualgit clone --depth 1 https://github.com/LingyiChen-AI/OpenSkillsWrote 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/lingyichen-ai/openskills/weekly-report-to-annual)<a href="https://agentmods.dev/skills/lingyichen-ai/openskills/weekly-report-to-annual"><img src="https://agentmods.dev/badge/skills/lingyichen-ai/openskills/weekly-report-to-annual/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/lingyichen-ai/openskills/weekly-report-to-annual"><img src="https://agentmods.dev/badge/skills/lingyichen-ai/openskills/weekly-report-to-annual.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 | $0.00022 | $0.00606 |
| Opus 5 | $0.00011 | $0.00303 |
| Sonnet 5 | $0.00004 | $0.00121 |
| Haiku 4.5 | $0.00002 | $0.00061 |
Grade A, and why
weekly-report-to-annual 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.
What it actually says
周报年报生成 Skill
你是一个专业的年度报告生成助手。你可以从用户的飞书邮箱中读取周报邮件，然后根据年度报告模板生成结构化的年度总结。
功能
- 读取周报邮件: 通过IMAP协议连接飞书邮箱，筛选标题包含"周报"的邮件
- 分析周报内容: 提取周报中的关键信息，包括工作成果、问题和计划
- 生成年度报告: 根据模板将周报内容汇总为年度报告
- 保存报告: 将生成的报告保存到本地
使用流程
- 用户提供飞书邮箱账号信息（邮箱地址和应用密码）
- 使用
fetch_emails脚本读取周报邮件 - 分析邮件内容，提取关键信息
- 参考年度报告模板（references/annual-report-template.md）
- 生成结构化的年度报告
- 使用
save_report脚本保存到本地
飞书邮箱配置说明
飞书邮箱 IMAP 服务器配置：
- IMAP服务器: imap.feishu.cn
- 端口: 993 (SSL)
- 需要在飞书管理后台开启IMAP服务并生成应用密码
注意事项
- 请确保已在飞书管理后台开启IMAP服务
- 使用应用密码而非登录密码
- 邮件读取可能需要一定时间，请耐心等待
- 生成的报告会保存为 Markdown 格式
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 75 lines · 22 tokens per session scan A eafb965547c8
weekly-report-to-annual is a skill published in the GitHub repository LingyiChen-AI/OpenSkills (68 stars, last pushed 7mo ago), licensed Apache-2.0. It adds 22 tokens to every session and 606 once invoked, about $0.0001 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.
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