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 chuancyzhang/deepseek-cowork --skill buyback_program_reviewer_skillgit clone --depth 1 https://github.com/chuancyzhang/deepseek-coworkWrote 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/chuancyzhang/deepseek-cowork/buyback_program_reviewer_skill)<a href="https://agentmods.dev/skills/chuancyzhang/deepseek-cowork/buyback_program_reviewer_skill"><img src="https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/buyback_program_reviewer_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/chuancyzhang/deepseek-cowork/buyback_program_reviewer_skill"><img src="https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/buyback_program_reviewer_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 | $0.00046 | $0.01152 |
| Opus 5.5 | $0.00018 | $0.00461 |
| Sonnet 5.5 | $0.00009 | $0.00230 |
| Haiku 4.5 | $0.00005 | $0.00115 |
Grade A, and why
buyback_program_reviewer_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 1mo 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- market_sentiment_temperature_skill — 86% identical, 149 lines differ
What it actually says
Buyback Program Reviewer Skill
数据依赖与执行前置条件
推荐使用万得 wind-mcp-skill 获取底层数据。执行前先检查本地是否已有 wind-mcp-skill；若没有，提示用户安装：
Cowork 适配：所需子 Skill 已随
wind-aifinmarket固定快照内置，不执行安装或在线更新命令。
技能定位
本技能用于评审公司回购计划的真实质量，重点回答“这次回购到底有多大、是否真能执行、管理层为什么现在做、对每股价值和市场信号的影响有多强”。输出重点不是把公告原文复述一遍，而是判断回购是实质利好、常规姿态，还是更多偏展示性动作。
执行流程
Step 1：确认回购条款与基本事实
先把回购计划的关键条款梳理清楚，至少包括：
- 回购总金额或股数上限
- 回购期限
- 回购方式
- 资金来源
- 是否注销、用于股权激励、员工持股或其他用途
若公告只有授权框架而无明确执行安排，应明确标注。
Step 2：衡量回购规模是否有实质意义
回购是否重要，首先取决于规模。重点判断：
- 相对于公司市值、流通股本的占比
- 相对于年度自由现金流和账上现金的压力
- 与历史回购规模相比是升级、常规还是象征性
- 与同业资本配置方式相比是否突出
Step 3：分析管理层为什么现在宣布回购
进一步判断回购背后的核心动因，常见包括：
- 管理层认为估值低估
- 需要稳定市场信心或修复预期
- 缺乏更高回报的再投资机会
- 对冲股权激励摊薄
- 资本结构管理或股东回报政策调整
动因分析应尽量结合公司当前经营阶段，而不是套用固定模板。
Step 4：区分“授权回购”与“实际执行”
很多回购计划存在执行不确定性，需要重点评估：
- 公司过去回购承诺的兑现度如何
- 当前现金流和资产负债表是否支持持续执行
- 是否存在监管、窗口期或其他技术约束
- 回购用途是否会弱化对股东的真实增厚效果
Step 5：映射到每股价值与投资逻辑
把回购从公告层翻译成研究层，至少回答：
- 对每股收益、股本结构和股东回报的潜在影响
- 是否改变当前估值支撑
- 是强化长期逻辑，还是仅提供短期情绪支撑
- 哪些情况下回购计划可能被市场忽略
Step 6：整合成回购评审成稿
最终输出应帮助使用者判断“这次回购值不值得当真”，而不是停留在公告摘要层面。
输出结构
{股票名称}回购评审（{YYYY-MM-DD}）
一、30 秒结论
- 计划强度：{强 / 中 / 弱}
- 核心判断：{一句话}
- 最重要的支持点：{一句话}
- 最需要警惕的地方：{一句话}
二、回购关键条款
| 项目 | 内容 | 评审 |
|---|---|---|
| 回购规模 | {内容} | {说明} |
| 回购期限 | {内容} | {说明} |
| 资金来源 | {内容} | {说明} |
| 回购用途 | {内容} | {说明} |
三、为什么现在做回购
- {动因 1}
- {动因 2}
- {动因 3}
四、真实利好程度判断
- 对每股价值的意义：{内容}
- 对市场情绪的意义：{内容}
- 执行落地难点：{内容}
五、后续跟踪清单
- {跟踪项 1}
- {跟踪项 2}
- {跟踪项 3}
质量要求
- 必须区分“宣布回购”与“有效执行”，不能把授权等同于兑现。
- 回购规模必须放到市值、现金流和股本背景中解读。
- 应同时分析股东回报意义与管理层动机，避免单一视角。
- 若回购主要用于对冲摊薄，应明确说明其边际利好有限。
- 输出要回答“这次回购是不是高质量资本配置动作”。
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.
- 1mo ago First seen · 126 lines · 46 tokens per session scan A 90eb2bfa770b
buyback_program_reviewer_skill is a skill published in the GitHub repository chuancyzhang/deepseek-cowork (18 stars, last pushed today), licensed Apache-2.0. It adds 46 tokens to every session and 1,152 once invoked, about $0.0002 per session on Opus 5.5. 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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