policy_headline_interpreter_skill

policy_headline_interpreter_skill is a skill for Claude Code, Codex from chuancyzhang/deepseek-cowork. It costs 63 tokens per session (1,319 once invoked), scanned A, a copy of moat_strength_review_skill, Apache-2.0.

A policy-news analysis guide that traces how government decisions may affect industries, market themes, and individual stocks. It separates genuine policy support from short-lived noise.

In plain words
What is it for?
Use it to assess policy news, identify possible beneficiaries, and judge whether a sector move has a credible catalyst.
Why use it?
Policy headlines can move prices without changing business results. This helps clarify the likely impact and the uncertainty around putting the policy into practice.

Skill for Claude CodeCodex

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

Good fit Use it to assess policy news, identify possible beneficiaries, and judge whether a sector move has a credible catalyst.

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

README.md
[![agentmods](https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/policy_headline_interpreter_skill/github.svg)](https://agentmods.dev/skills/chuancyzhang/deepseek-cowork/policy_headline_interpreter_skill)
Your own site
<a href="https://agentmods.dev/skills/chuancyzhang/deepseek-cowork/policy_headline_interpreter_skill"><img src="https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/policy_headline_interpreter_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.

agentmods 80×15 button for policy_headline_interpreter_skill

Your own site · 80×15
<a href="https://agentmods.dev/skills/chuancyzhang/deepseek-cowork/policy_headline_interpreter_skill"><img src="https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/policy_headline_interpreter_skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 63 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,319 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 88% copy Near-identical to another mod 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 $0.00063 $0.01319
Opus 5.5 $0.00025 $0.00528
Sonnet 5.5 $0.00013 $0.00264
Haiku 4.5 $0.00006 $0.00132

Measured 1mo ago against content hash e4353c60fbff, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

policy_headline_interpreter_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.

Origin

This is a copy

88% identical to moat_strength_review_skill — 157 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.

ai_skills/wind-aifinmarket/skills/policy_headline_interpreter_skill/SKILL.md · 132 lines

What it actually says

Policy Headline Interpreter 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

本技能用于解读政策头条对市场的影响,回答“这条政策新闻是真的增量信号,还是旧闻重提;影响会先落在哪些行业和公司;从新闻到落地之间还有哪些不确定性”。输出重点不是把政策原文转述一遍,而是帮助使用者在最短时间内完成政策定性、受益映射和风险判断。

执行流程

Step 1:确认政策来源、级别与状态

先把政策消息本身界定清楚:

  • 来源是正式文件、会议表述、权威媒体还是传闻型信息
  • 是顶层方向性表态,还是具体执行规则
  • 当前处于征求意见、正式发布、执行推进还是口径澄清阶段
  • 信息是否为新增,还是市场已经交易过的内容

若来源和状态不清晰,必须先把可信度和正式程度说明白。

Step 2:拆解政策目标与关键约束

政策解读不能只看表面提法,还要回答:

  • 政策试图解决什么问题
  • 受益方向是需求刺激、供给约束、融资改善还是监管放松
  • 执行中最重要的门槛、节奏和约束条件是什么
  • 哪些表述是原则性信号,哪些才是实质性变化

Step 3:映射受影响的行业、主题与公司

在目标明确后,分层映射影响范围:

  • 直接受益行业
  • 间接受益或边际受益行业
  • 可能受约束或受损的行业
  • 核心受益公司与边缘映射公司

映射时要区分“政策直接触达”和“市场情绪外溢”,不能混为一谈。

Step 4:分析影响路径与兑现节奏

进一步说明这条政策为何影响市场,以及影响如何逐步兑现:

  • 是先影响预期,再影响订单、投资、价格或盈利
  • 哪些影响可以短期体现,哪些需要更长时间验证
  • 市场当前更可能交易政策想象,还是现实兑现
  • 若后续执行力度不足,哪些方向最容易回吐

Step 5:评估交易价值与误判风险

政策消息容易被过度放大,因此要重点指出:

  • 哪部分影响已经被市场提前反映
  • 哪些受益逻辑证据较强,哪些只是概念扩散
  • 最容易出现的误判是把口号当结果、把边缘映射当核心受益
  • 后续最关键的验证节点是什么

Step 6:形成政策头条解读成稿

最终输出应帮助使用者快速完成“政策定性 + 影响映射 + 节奏判断 + 风险控制”。正文只保留事实、影响链条、受益排序和后续验证点。

输出结构


{政策主题}头条解读({YYYY-MM-DD})

一、30 秒结论

  • 政策性质:{方向性信号 / 实质性增量 / 旧闻重提 / 噪音扰动}
  • 直接受益方向:{内容}
  • 最大不确定性:{内容}
  • 当前建议:{重点跟踪 / 谨慎乐观 / 等待细则 / 避免泛化}

二、政策事实卡片

项目 内容
来源 {内容}
级别 {内容}
状态 {内容}
关键表述 {内容}
是否新增 {是 / 否 + 说明}

三、影响映射

  • 直接受益行业/主题:{内容}
  • 间接受益方向:{内容}
  • 可能受压制方向:{内容}
  • 核心受益公司 vs 边缘映射公司:{内容}

四、影响路径与兑现节奏

  • 短期影响:{内容}
  • 中期影响:{内容}
  • 兑现所需条件:{内容}

五、误判风险与验证节点

  • 最容易被误判的点:{内容}
  • 后续关键验证:{内容}
  • 可能推翻当前判断的因素:{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

  1. 政策解读必须先确认来源、级别和状态,不能把所有消息同等对待。
  2. 要区分正式增量政策、方向性表态与市场噪音。
  3. 影响映射必须区分核心受益和边缘映射,避免概念扩散失控。
  4. 需要明确执行约束和兑现节奏,防止把政策口号直接写成业绩结果。
  5. 输出要帮助使用者完成快速政策定性与后续验证,而不是改写新闻稿。
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 · 132 lines · 63 tokens per session scan A e4353c60fbff

Subscribe to this mod's changes

policy_headline_interpreter_skill is a skill published in the GitHub repository chuancyzhang/deepseek-cowork (18 stars, last pushed today), licensed Apache-2.0. It adds 63 tokens to every session and 1,319 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 88% identical to moat_strength_review_skill, differing in 157 lines, and is treated as a copy.

Related

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.

HKUDS/Vibe-Trading · 39 tokens

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…

himself65/finance-skills · 110 tokens

strategy-pivot-designer

Detect backtest iteration stagnation and generate structurally different strategy pivot proposals when parameter tuning reaches a local optimum.

tradermonty/claude-trading-skills · 28 tokens

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…

hashgraph-online/awesome-codex-plugins · 93 tokens

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.

nirholas/three.ws · 54 tokens

recipe-daily-pnl-report

Generate a daily profit and loss summary from trades and balances.

krakenfx/kraken-cli · 19 tokens