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 guidance_change_impact_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/guidance_change_impact_skill)<a href="https://agentmods.dev/skills/chuancyzhang/deepseek-cowork/guidance_change_impact_skill"><img src="https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/guidance_change_impact_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/guidance_change_impact_skill"><img src="https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/guidance_change_impact_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 | $0.00056 | $0.01332 |
| Opus 5.5 | $0.00022 | $0.00533 |
| Sonnet 5.5 | $0.00011 | $0.00266 |
| Haiku 4.5 | $0.00006 | $0.00133 |
Grade A, and why
guidance_change_impact_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 — 199 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.
What it actually says
Guidance Change Impact 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
本技能用于解读公司管理层对未来经营指引的变动,重点回答“这次上修或下修究竟意味着什么、可信度高不高、影响会停留在情绪层还是会穿透到估值与逻辑层”。输出重点不是只翻译指引文字,而是把变动幅度、口径变化、背后动因和后续影响链条讲清楚。
执行流程
Step 1:确认变动对象与原始口径
先确认本次变动的是哪类指引,以及基准口径是什么。优先厘清:
- 是收入、利润、利润率、现金流、资本开支还是订单指引
- 是全年指引、季度指引,还是阶段性经营展望
- 本次是正式调整,还是管理层在交流中边际修正表述
- 新旧口径是否可直接比较
如果口径有变化,必须先解释可比性,再讨论方向。
Step 2:衡量变动幅度与市场预期差
把指引变化放到正确坐标里看,重点包括:
- 变动绝对幅度和相对幅度
- 与市场原有预期相比是超预期、符合还是不及
- 与公司历史沟通风格相比是激进、常规还是保守
- 当前估值是否已经部分计入这类调整
这一步的目标是判断“变化本身大不大”和“市场是否已经提前反应”。
Step 3:拆解变动背后的驱动因素
进一步判断此次指引变化来自哪里,常见来源包括:
- 需求变化、价格变化、订单节奏变化
- 成本、费用、供应链或汇率扰动
- 新产品、新项目、新区域扩张的兑现或延迟
- 管理层风险偏好变化或沟通策略变化
- 一次性项目对短期口径造成影响
应优先抓主要驱动,不要把所有可能因素平均分配。
Step 4:评估指引可信度与可持续性
同样的上修或下修,含金量可能完全不同。需要重点判断:
- 管理层过去给指引是否稳定可信
- 本次变化是否有足够经营证据支撑
- 是基于已确认订单,还是基于前瞻假设
- 哪些关键变量仍然脆弱,可能导致再次修正
Step 5:映射到估值、预期与投资逻辑
把指引变化从“口径变化”翻译成“投资含义”,至少回答:
- 这会改变市场对增长、利润或质量的哪部分判断
- 估值锚点是否需要同步调整
- 原有看多或看空逻辑哪一边被强化
- 这次变化更像拐点确认、噪音扰动还是一次性修正
Step 6:整合成变动解读成稿
最终输出应帮助使用者快速看懂“这次调指引有没有实质意义”,不展示中间搜集过程或内部草稿。
输出结构
{股票名称}指引变动解读({YYYY-MM-DD})
一、30 秒结论
- 变动方向:{上修 / 下修 / 维持}
- 变动含义:{一句话}
- 可信度判断:{高 / 中 / 低}
- 对逻辑的影响:{强化 / 中性 / 削弱}
二、指引变动摘要
| 项目 | 原指引 | 新指引 | 变动幅度 | 初步解读 |
|---|---|---|---|---|
| {项目1} | {内容} | {内容} | {内容} | {说明} |
| {项目2} | {内容} | {内容} | {内容} | {说明} |
三、变动背后的核心原因
- 原因 1:{内容}
- 原因 2:{内容}
- 原因 3:{内容}
四、市场为什么会在意
- {影响链条 1}
- {影响链条 2}
- {影响链条 3}
五、可信度与可持续性评估
- 支持证据:{内容}
- 不确定性:{内容}
- 再次修正风险:{内容}
六、后续跟踪清单
- {跟踪项 1}
- {跟踪项 2}
- {跟踪项 3}
质量要求
- 先解释变动口径和幅度,再下结论,避免跳步。
- 必须区分“表述变化”与“经营趋势变化”。
- 可信度评估不能省略,否则解读会失去判断价值。
- 若新旧口径不可比,应明确指出,不做强行比较。
- 结论要落到投资含义,而不是停留在管理层话术层面。
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 · 56 tokens per session scan A eea0d19b0390
guidance_change_impact_skill is a skill published in the GitHub repository chuancyzhang/deepseek-cowork (18 stars, last pushed today), licensed Apache-2.0. It adds 56 tokens to every session and 1,332 once invoked, about $0.0002 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 199 lines, and is treated as a copy.
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