conference_call_takeaway_skill

conference_call_takeaway_skill is a skill for Claude Code, Codex from chuancyzhang/deepseek-cowork. It costs 50 tokens per session (1,287 once invoked), scanned A, original, Apache-2.0.

A tool for extracting new information, changes in management tone, question themes, and warning signs from an earnings call. An earnings call is a company's discussion of its financial results with investors and analysts.

In plain words
What is it for?
It is for reviewing earnings calls, summarising management commentary, and identifying risks or changing signals.
Why use it?
It helps update an investment view quickly after listening to a call or reading its notes.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It is for reviewing earnings calls, summarising management commentary, and identifying risks or changing signals.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/chuancyzhang/deepseek-cowork/conference_call_takeaway_skill
Install

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.

Any agent
npx skills add chuancyzhang/deepseek-cowork --skill conference_call_takeaway_skill
Clone the repo
git clone --depth 1 https://github.com/chuancyzhang/deepseek-cowork

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for conference_call_takeaway_skill

README.md
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Your own site
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<a href="https://agentmods.dev/skills/chuancyzhang/deepseek-cowork/conference_call_takeaway_skill"><img src="https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/conference_call_takeaway_skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 50 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,287 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00050 $0.01287
Opus 5.5 $0.00020 $0.00515
Sonnet 5.5 $0.00010 $0.00257
Haiku 4.5 $0.00005 $0.00129

Measured 1mo ago against content hash baab000a1741, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

conference_call_takeaway_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.

ai_skills/wind-aifinmarket/skills/conference_call_takeaway_skill/SKILL.md · 130 lines

What it actually says

Conference Call Takeaway 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

本技能用于从业绩会或类似管理层交流材料中提炼真正有价值的新信息,重点回答“管理层到底新增说了什么、哪些语气和措辞值得警惕、分析师最追问什么、哪些内容会改变后续研究重点”。输出重点不是会议逐段转述,而是帮助使用者抓住会后最值得更新的判断。

执行流程

Step 1:确认会议范围与阅读目标

先确认对应的是哪次业绩会、投资者交流会或经营更新会,并明确用户最关心的用途:

  • 快速复盘会议重点
  • 判断管理层说法是否强化原观点
  • 提炼团队分享纪要
  • 寻找会后需要继续验证的风险点

若用户未说明,默认按“会后快速更新研究判断”展开。

Step 2:先抓新增信息,再看重复表述

会议材料通常包含大量重复表述,应优先筛出真正有新增价值的部分:

  • 对业绩、需求、订单、利润率等的边际更新
  • 对前次未明确问题的补充回答
  • 对市场争议点的正面回应或回避
  • 对未来节奏、优先事项、资本配置的最新表态

如果某段内容只是重复公开口径,应降级处理,避免占据核心摘要。

Step 3:识别管理层语气与信号变化

除了字面内容,还要关注表达方式变化,包括:

  • 相比上次更乐观、更谨慎或更防守
  • 对某类问题更愿意展开,还是刻意收缩
  • 对风险描述更具体,还是用笼统表述遮掩不确定性
  • 是否出现前后不一致、模糊化或转移焦点的情况

这一步的目标是捕捉“说了什么”和“怎么说”之间的差异。

Step 4:提炼问答环节的真正焦点

分析师或投资者在问答里反复追问的内容,通常更接近市场核心分歧。应重点总结:

  • 被反复追问的变量是什么
  • 管理层回答是否直接、充分、可验证
  • 哪些问题被回答得很强,哪些仍然含糊
  • 是否有某个问题暴露出管理层准备不足或市场担忧加深

Step 5:沉淀会后更新与警讯

在会议读完后,需要明确:

  • 哪些原有观点被强化
  • 哪些新信息要求修正研究框架
  • 哪些风险虽未完全暴露,但已经出现苗头
  • 后续最需要继续核验的经营变量是什么

Step 6:整合成会后摘要成稿

最终输出应是一份可直接转发、可直接用于内部讨论的会后提炼,不展示逐段阅读过程或原始摘抄堆叠。

输出结构


{股票名称}业绩会提炼({YYYY-MM-DD})

一、30 秒结论

  • 本场会议最重要的新信息:{一句话}
  • 管理层整体语气:{更积极 / 基本稳定 / 转谨慎}
  • 最值得警惕的信号:{一句话}
  • 会后判断:{逻辑强化 / 有待验证 / 风险上升}

二、会议新增信息

  • 新增信息 1:{内容}
  • 新增信息 2:{内容}
  • 新增信息 3:{内容}

三、管理层语气变化

观察点 本次表现 含义
需求表述 {内容} {说明}
利润率/成本表述 {内容} {说明}
未来节奏表述 {内容} {说明}

四、问答焦点与回答质量

  • 市场最关心的问题:{内容}
  • 回答最充分的问题:{内容}
  • 回答最模糊的问题:{内容}

五、会后警讯与后续验证

  • {警讯 1}
  • {警讯 2}
  • {后续验证点}

六、研究更新建议

  • 应更新的判断:{内容}
  • 暂不下结论的部分:{内容}

质量要求

  1. 必须优先呈现新增信息,不把会议重复内容当作重点。
  2. 不能只摘抄管理层原话,要转化成研究意义。
  3. 问答环节的焦点和回答质量必须单独处理,因为它通常最接近市场分歧。
  4. 语气变化要结合上下文判断,避免把正常措辞差异误判为趋势变化。
  5. 输出应服务“会后更新观点”,而不是沦为冗长会议纪要。
Changes

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.

  1. 1mo ago First seen · 130 lines · 50 tokens per session scan A baab000a1741

Subscribe to this mod's changes

conference_call_takeaway_skill is a skill published in the GitHub repository chuancyzhang/deepseek-cowork (18 stars, last pushed today), licensed Apache-2.0. It adds 50 tokens to every session and 1,287 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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