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 vcp_breakout_scan_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/vcp_breakout_scan_skill)<a href="https://agentmods.dev/skills/chuancyzhang/deepseek-cowork/vcp_breakout_scan_skill"><img src="https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/vcp_breakout_scan_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/vcp_breakout_scan_skill"><img src="https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/vcp_breakout_scan_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 | $0.00072 | $0.01635 |
| Opus 5.5 | $0.00029 | $0.00654 |
| Sonnet 5.5 | $0.00014 | $0.00327 |
| Haiku 4.5 | $0.00007 | $0.00163 |
Grade A, and why
vcp_breakout_scan_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.
How it starts
The opening of the file, as written. The whole thing — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.
VCP Breakout Scan 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
本技能用于寻找波动逐步收缩、供给逐步减弱、价格结构趋于成熟的突破预备股。输出重点不是泛泛寻找整理形态，而是识别哪些股票已经进入“压缩波动、等待释放”的关键阶段，以及这种结构是否具备较好的后续突破条件。
功能简介
本技能的核心功能是：筛选波动收敛充分、具备突破条件的 VCP 预备股。
它强调把波动压缩、回调幅度递减、量能收敛、供需改善和市场环境整合起来，帮助使用者建立一组高质量的突破预备股名单。
使用场景
- 用户采用波动收缩策略寻找主升前的准备期股票。
- 强势股回调后，需要判断哪些已经完成充分洗盘。
- 团队要筛选“离突破只差一步”的技术结构候选。
- 需要将图形观察转化为纪律化的观察清单。
工作原则
- VCP 结构的核心是波动和供给收敛，不能只看价格横盘。
- 必须检查回调幅度是否逐步收窄，而不是一次大跌后的静止。
- 量能变化与结构位置要同步判断，不能把成交极低简单理解为健康。
- 需要结合基本面或催化背景确认其不是纯技术噪音。
- 正文中不显式提及内部实现方式。
执行流程
Step 1：确认筛选对象与时间周期
先明确扫描目标是：
- 全市场 VCP 预备股
- 某个板块或风格中的结构筛选
- 前期强势股的二次整理
- 还是自选股里的重点技术结构复查
同时确认用户关注的是日线级别还是更高周期的收缩结构。
Step 2：识别前置上涨基础
VCP 结构通常出现在已有上涨基础的股票上，因此要先确认：
- 股票在进入收缩期前是否已经存在清晰上涨段
- 前期上涨是否具备基本面、题材或资金主线支持
- 是否属于真正的强势股整理，而非长期弱势横盘
没有前置强势基础的横盘，很难构成高质量 VCP 候选。
Step 3：检查波动是否逐级收缩
这是本技能最核心的判断环节。要重点观察：
- 每一轮回调幅度是否较上一轮更浅
- 每次修复后的高点是否更接近前高
- 日内和区间波动是否呈现压缩趋势
- 整理后期是否明显减少剧烈震荡
真正的波动收缩应体现“卖压在减少”，而不是“交投停滞”。
Step 4：检查量能是否同步收敛
波动收缩若没有量能配合，可信度会明显下降。应判断：
- 回调阶段的量能是否逐步萎缩
- 反弹阶段是否偶有适度放量显示承接
- 临近关键位时是否出现量能温和回升
- 是否存在某一次放量下跌破坏供需平衡
Step 5：定义关键位置与触发条件
对每只候选，需要明确：
- 真正的突破触发位在哪里
- 哪个价格区域属于最关键的供需转折点
- 突破时需要出现什么量价确认
- 如果未能有效站稳，应如何定义失败
Step 6：补充基本面或催化支撑
高质量 VCP 候选，往往不只是技术结构漂亮。还要确认：
- 是否存在业绩、产品、题材、订单或行业景气支撑
- 板块是否处于强化周期
- 若结构成立，市场是否有理由给予持续关注
Step 7：按成熟度分层排序
将候选分为：
- 结构成熟、接近触发的重点对象
- 收缩正在形成、仍需时间的中间对象
- 结构看似相似但供需不够健康的谨慎对象
Step 8：整合成波缩突破成稿
最终输出应帮助使用者知道“哪几只票的波动收缩最有质量、等什么、怎么确认、何时放弃”。正文只保留判断与观察框架。
输出结构
波缩突破候选筛选（{YYYY-MM-DD}）
一、30 秒结论
- 最成熟的 VCP 候选：{名称列表}
- 当前结构状态：{接近触发 / 仍在收缩 / 结构待修复}
- 环境匹配度：{高 / 中 / 低}
- 最大风险：{一句话}
二、候选池总览
| 股票 | 前置强势基础 | 波动收缩质量 | 量能收敛质量 | 触发准备度 | 优先级 |
|---|---|---|---|---|---|
| {标的1} | {强/中/弱} | {高/中/低} | {高/中/低} | {高/中/低} | {A/B/C} |
| {标的2} | {等级} | {等级} | {等级} | {等级} | {等级} |
三、重点候选拆解
{股票名称}
- 结构特征：{内容}
- 关键位置：{内容}
- 理想确认信号：{内容}
- 当前仍欠缺的条件：{内容}
- 失效边界：{内容}
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 · 164 lines · 72 tokens per session scan A 8de00370b05a
vcp_breakout_scan_skill is a skill published in the GitHub repository chuancyzhang/deepseek-cowork (18 stars, last pushed today), licensed Apache-2.0. It adds 72 tokens to every session and 1,635 once invoked, about $0.0003 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 2026-09-04.
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