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 pullback_opportunity_finder_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/pullback_opportunity_finder_skill)<a href="https://agentmods.dev/skills/chuancyzhang/deepseek-cowork/pullback_opportunity_finder_skill"><img src="https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/pullback_opportunity_finder_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/pullback_opportunity_finder_skill"><img src="https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/pullback_opportunity_finder_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 | $0.00068 | $0.01951 |
| Opus 5.5 | $0.00027 | $0.00780 |
| Sonnet 5.5 | $0.00014 | $0.00390 |
| Haiku 4.5 | $0.00007 | $0.00195 |
Grade A, and why
pullback_opportunity_finder_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.
This is a copy
84% identical to breakout_candidate_finder_skill — 191 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 181 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pullback Opportunity Finder 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
本技能用于筛选“上涨主逻辑仍在、趋势尚未破坏，但价格经历阶段性回调”的候选股。输出重点不是机械寻找跌幅较大的股票，而是识别哪些回调属于健康整理、哪些只是弱势反弹前的下跌中继，从而帮助使用者把“低吸”建立在趋势和结构判断之上。
功能简介
本技能的核心功能是：寻找回调充分但趋势未破坏的候选股，定位低吸观察区。
它强调把趋势完整性、回调深度、承接信号、催化延续性和风险边界合并评估，避免把所有下跌都误认成机会。
使用场景
- 强势板块回调后，需要判断哪些个股仍值得继续跟踪。
- 用户希望寻找“二次上车”而不是追高买入的机会。
- 交易团队需要在日内或日终更新低吸观察池。
- 已有持仓的用户想区分正常回调与趋势转弱。
工作原则
- 回调机会的前提是原有主趋势仍然有效，不能脱离趋势单看跌幅。
- 必须区分“强势整理”“趋势破坏”“情绪出清”三种回调性质。
- 所有低吸结论都应附带观察区间、确认信号与止错边界。
- 若回调缺乏承接或催化被证伪，应优先视为风险而非机会。
- 正文只呈现分析结果，不显式描述内部实现细节。
执行流程
Step 1：确认股票池与回调定义
先明确本次寻找的是哪一类回调机会：
- 是前期领涨股的技术性回踩
- 是趋势股在消息冲击后的快速修复机会
- 是板块退潮后寻找仍具韧性的少数强势股
- 还是中期主升浪中的阶段性洗盘机会
同时要确认用户关注的是日线级别、周线级别还是更短周期的回调。
Step 2：确认原趋势是否成立
对候选股票，先回看回调前的上涨是否具有真实趋势基础：
- 是否存在连续的强势结构而非脉冲拉升
- 是否有业绩、景气、政策、题材强化等主线支持
- 上涨阶段的量价关系是否健康
- 历史上该股是否具备回踩后继续走强的行为特征
如果原先的上涨本身缺乏趋势质量，后续回调也不应轻易定义为机会。
Step 3：评估回调深度与节奏是否健康
健康回调的重点不在于“跌得够多”，而在于“退得有序”。要观察：
- 回调幅度相对于前一段上涨是否仍在可接受区间
- 回调速度是急跌出清，还是温和缩量整理
- 回调过程是否跌破重要均线、平台下沿或关键低点
- 下跌期间是否出现明显放量失控或筹码踩踏
若回调深度过深、节奏失衡，应优先转为风险观察而非低吸候选。
Step 4：寻找支撑区与承接信号
回调机会要落到具体价格区与行为信号上。重点确认：
- 哪个区间可能形成有效支撑
- 回落到支撑区时是否出现缩量企稳、下影修复或主动承接
- 同板块个股是否同步出现回稳迹象
- 若存在反抽，反抽质量是否显示资金愿意重新介入
没有承接，就只有下跌；只有价格接近支撑，并不等于机会已经出现。
Step 5：检验催化是否仍然有效
低吸成立的关键，是原有主线没有被根本破坏。要重新核验：
- 推动上涨的核心叙事是否还成立
- 回调是否源于阶段兑现，而非基本面走弱
- 未来一段时间是否仍有继续强化逻辑的事件窗口
- 市场偏好是否已从该风格切换离场
如果催化已明显钝化或反向变化，应降低低吸优先级。
Step 6：区分“观察区”与“确认点”
优质低吸并不意味着到位就买，而是要把过程拆成两个层次：
- 观察区：股价进入值得重点盯的价格区域
- 确认点：出现量价修复、板块共振或重新走强的证据
同时要写清楚：
- 何种情况下可以升级跟踪级别
- 何种情况下应放弃原有低吸判断
- 若错过最优位置，是否还有二次介入机会
Step 7：形成候选排序与策略建议
将候选按“趋势完整性 + 回调健康度 + 承接质量 + 催化延续性”综合排序，明确区分：
- 可积极观察的回调机会
- 只适合等待确认的观察对象
- 回调看似充分但实则不应低吸的风险对象
Step 8：整合成回调机会成稿
最终输出应帮助使用者知道“哪些票能等、等到哪里、看什么信号、什么情况下不再等”。正文只呈现结论、证据和观察框架，不展示中间草稿。
输出结构
回调机会筛选（{YYYY-MM-DD}）
一、30 秒结论
- 最值得关注的回调对象：{名称列表}
- 当前最健康的回调类型：{温和整理 / 快速出清 / 平台回踩}
- 整体策略倾向：{积极等确认 / 只做观察 / 暂不低吸}
- 最大风险点：{一句话}
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 · 181 lines · 68 tokens per session scan A 79a2cc240677
pullback_opportunity_finder_skill is a skill published in the GitHub repository chuancyzhang/deepseek-cowork (18 stars, last pushed today), licensed Apache-2.0. It adds 68 tokens to every session and 1,951 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 84% identical to breakout_candidate_finder_skill, differing in 191 lines, and is treated as a copy.
Other skills, from other repositories
sector-rotation
An analysis framework for comparing industries in the Chinese A-share stock market, using business conditions, price momentum, valuation, and money flows. It produces rankings and higher- or lower-allocation suggestions.
twitter-reader
Read Twitter/X for financial research through opencli: the user's home timeline, tweet search, trending topics, bookmarks, a user's recent tweets, threads, articles, profiles, followers and following, and notifications. Use this skill whenever the user wants to know what people are saying on Twitter/X or fintwit about…
strategy-pivot-designer
Detect backtest iteration stagnation and generate structurally different strategy pivot proposals when parameter tuning reaches a local optimum.
energy-procurement
Codified expertise for electricity and gas procurement, tariff optimization, demand charge management, renewable PPA evaluation, and multi-facility energy cost management. Informed by energy procurement managers with 15+ years experience at large commercial and industrial consumers. Includes market structure analysis…
airdrop-hunting-guide
Guide to finding and qualifying for crypto airdrops — eligibility criteria, farming strategies, on-chain activity requirements, Sybil detection avoidance, and tracking tools. Use when helping users understand airdrops, check eligibility, or plan participation strategies.
recipe-daily-pnl-report
Generate a daily profit and loss summary from trades and balances.