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 institutional_position_shift_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/institutional_position_shift_skill)<a href="https://agentmods.dev/skills/chuancyzhang/deepseek-cowork/institutional_position_shift_skill"><img src="https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/institutional_position_shift_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/institutional_position_shift_skill"><img src="https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/institutional_position_shift_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 | $0.00058 | $0.01255 |
| Opus 5.5 | $0.00023 | $0.00502 |
| Sonnet 5.5 | $0.00012 | $0.00251 |
| Haiku 4.5 | $0.00006 | $0.00126 |
Grade A, and why
institutional_position_shift_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.
What it actually says
Institutional Position Shift 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
本技能用于分析机构持仓变化，回答“哪些方向被机构明显增配或减配、这些变化体现了什么共识、是高信念加仓还是被动调整、对后续市场和个股意味着什么”。输出重点不是简单比较持股数量，而是解释持仓变化背后的偏好迁移和潜在影响。
执行流程
Step 1：确认样本范围、报告周期与解读口径
先明确本次研究的样本和边界：
- 观察的是哪类机构
- 覆盖的是单只股票、一个行业，还是更大的股票池
- 对应的是哪个报告周期
- 用户更关心机构共识变化，还是某几家核心机构的动作
同时要提醒使用者：机构持仓披露通常存在时间滞后，结论应结合这一点解读。
Step 2：梳理持仓变化的总体特征
先从整体上判断：
- 哪些行业或风格被集中增配
- 哪些方向被系统性减配
- 机构持仓是更集中还是更分散
- 原有热门方向是否仍在强化，还是开始松动
这一阶段的目标是先把大方向看清楚。
Step 3：拆解重点公司和代表性变化
进一步聚焦最有代表性的持仓变化：
- 哪些公司被明显增持
- 哪些公司被明显减持
- 哪些变化来自原有核心仓位继续加码
- 哪些变化体现机构从旧主线转向新主线
应优先挑选能代表共识变化的样本，而不是机械罗列全部名单。
Step 4：区分高信念调仓与被动变化
机构持仓变化并不都具有同样含义，需要进一步判断：
- 是主动表达观点，还是被动因涨跌、基准调整或流动性原因而变化
- 加仓是否伴随更高集中度
- 减仓是否代表观点转弱，还是阶段性兑现
- 是否存在机构之间分歧加大而非单一共识强化
Step 5：提炼对行业、主题与个股的含义
围绕调仓结果，说明：
- 哪些行业或主题正在获得机构共识支持
- 哪些公司可能因机构增持得到估值与流动性支撑
- 哪些公司若出现机构撤退，风险应如何评估
- 后续需要通过哪些经营或市场信号验证机构判断是否正确
Step 6：形成机构调仓洞察成稿
最终输出应帮助使用者理解机构共识在往哪里走，以及该如何看待这些披露信息。正文只保留持仓变化、偏好解读、局限说明和验证框架。
输出结构
机构调仓洞察（{报告周期}）
一、30 秒结论
- 本期机构偏好方向：{内容}
- 最明显的增配线索：{内容}
- 最明显的减配线索：{内容}
- 当前含义：{共识强化 / 分歧加大 / 结构切换}
二、总体持仓变化
| 维度 | 当前表现 | 判断 |
|---|---|---|
| 行业层面 | {内容} | {判断} |
| 风格层面 | {内容} | {判断} |
| 集中度变化 | {内容} | {判断} |
三、重点公司变化
- 明显增持公司：{内容}
- 明显减持公司：{内容}
- 最具代表性的调仓动作：{内容}
四、调仓性质判断
- 高信念主动调仓：{内容}
- 可能的被动变化：{内容}
- 机构分歧点：{内容}
五、市场含义与风险提示
- 对行业/主题的含义：{内容}
- 对个股的含义：{内容}
- 解读局限：{内容}
六、后续观察清单
- {观察点 1}
- {观察点 2}
- {观察点 3}
质量要求
- 机构持仓分析必须提醒披露滞后，避免把历史持仓直接当成当前动作。
- 要区分主动高信念调仓与被动变化，提升解释可信度。
- 需同时覆盖行业、风格和重点个股三个层次。
- 若机构之间分歧明显，应明确写出，而不是强行概括成一致共识。
- 输出要帮助使用者理解机构偏好迁移，而不是停留在持股名单罗列。
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 · 131 lines · 58 tokens per session scan A 74d3fea3e2af
institutional_position_shift_skill is a skill published in the GitHub repository chuancyzhang/deepseek-cowork (18 stars, last pushed today), licensed Apache-2.0. It adds 58 tokens to every session and 1,255 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 2026-09-04.
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