peer_comparison_decision_skill

peer_comparison_decision_skill is a skill for Claude Code, Codex from chuancyzhang/deepseek-cowork. It costs 66 tokens per session (1,344 once invoked), scanned A, original, Apache-2.0.

A comparison guide for evaluating several companies in the same industry. It compares business quality, growth, profit, valuation, and possible future catalysts.

In plain words
What is it for?
Use it when choosing between stocks, ranking companies within an industry, or building a watchlist.
Why use it?
Choosing between similar companies requires weighing several differences at once. This helps identify the relatively stronger candidate and set a follow-up order.

Skill for Claude CodeCodex

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

Good fit Use it when choosing between stocks, ranking companies within an industry, or building a watchlist.

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

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/chuancyzhang/deepseek-cowork/peer_comparison_decision_skill"><img src="https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/peer_comparison_decision_skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 66 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,344 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 $0.00066 $0.01344
Opus 5.5 $0.00026 $0.00538
Sonnet 5.5 $0.00013 $0.00269
Haiku 4.5 $0.00007 $0.00134

Measured 1mo ago against content hash dce96608c997, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

peer_comparison_decision_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/peer_comparison_decision_skill/SKILL.md · 146 lines

What it actually says

Peer Comparison Decision 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

本技能用于在同一行业或同一主题内,对 2-5 家候选公司做横向比较,并输出可执行的相对排序与选择理由。重点不是把每家公司都重新写一遍,而是帮助使用者回答“如果只能优先研究或持有其中几家,应该先选谁、为什么”。

执行流程

Step 1:确认可比范围与比较目标

先明确比较对象是否真正可比,重点确认:

  • 所处赛道是否一致
  • 商业模式是否相近
  • 处于相似的发展阶段还是明显错位
  • 用户想比较的是短期交易机会还是中长期配置价值

若对象并不适合直接比较,应先说明可比性边界,再决定是否继续强行并列。

Step 2:建立统一比较框架

围绕用户真实决策,把比较维度标准化。常用维度包括:

  • 业务质量与竞争位置
  • 成长速度与成长确定性
  • 盈利能力与现金创造能力
  • 估值高低与预期要求
  • 近期催化与风险暴露

所有候选公司都按同一框架展开,避免某家公司只写故事、另一家公司只看数字。

Step 3:完成基础数据与事实对齐

收集每家公司的关键事实,并统一口径后放入对照表,特别注意:

  • 时间口径一致
  • 币种与单位一致
  • 估值方法口径一致
  • 对异常值和一次性因素进行说明

这一阶段的目标是把后续判断建立在同一坐标系之上。

Step 4:比较“业务质量”而不是只比较“数据高低”

除关键财务指标外,还要比较:

  • 核心产品与客户结构
  • 市场份额与竞争优势
  • 业务模式的抗波动能力
  • 管理执行与资本配置风格

若某家公司短期数据更亮眼,但业务稳定性明显更弱,应明确指出,不可被表面增速误导。

Step 5:比较“赔率”与“催化顺序”

真正的比选往往不只看谁更好,还要看谁更值得现在买入或优先跟踪。需重点判断:

  • 哪家公司好但已被充分定价
  • 哪家公司一般但预期差更大
  • 哪家公司短期有催化,哪家公司需要时间兑现
  • 哪家公司更适合观察,哪家公司更适合行动

Step 6:输出排序与决策建议

在完成横向比较后,给出明确排序,并说明:

  • 排名靠前的核心理由
  • 排名靠后的主要短板
  • 若只能研究一只、持有一只或短期交易一只,分别应如何选择

若结论取决于用户风格差异,也要明确把“成长型偏好”“价值型偏好”“交易型偏好”拆开说明。

输出结构


{行业/主题}同业比选({YYYY-MM-DD})

一、结论摘要

  • 最佳综合选择:{公司}
  • 最佳预期差选择:{公司}
  • 最适合继续观察:{公司}

二、统一比较表

公司 业务定位 增长 盈利 估值 近期催化 主要风险
{公司A} {描述} {描述} {描述} {描述} {描述} {描述}
{公司B} {描述} {描述} {描述} {描述} {描述} {描述}

三、相对强弱分析

业务质量

  • {谁更强,强在哪里}

成长质量

  • {谁更强,强在哪里}

估值赔率

  • {谁更有吸引力,原因是什么}

催化与时点

  • {谁更适合当下,原因是什么}

四、最终排序

排名 公司 结论
1 {公司} {理由}
2 {公司} {理由}
3 {公司} {理由}

五、决策建议

  • 如果只能先研究一只:{公司},因为 {理由}
  • 如果只能先跟踪一只:{公司},因为 {理由}
  • 如果只能先规避一只:{公司},因为 {理由}

质量要求

  1. 只比较真正可比的对象,必要时先写清不可比之处。
  2. 统一使用同一比较口径,避免数据和叙事各说各话。
  3. 输出重点是“相对强弱与排序”,不是多篇个股介绍拼接。
  4. 必须同时比较质量、估值和时点,不能只用单一指标排名。
  5. 若结论明显依赖投资风格,应把适用人群写清楚。
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 · 146 lines · 66 tokens per session scan A dce96608c997

Subscribe to this mod's changes

peer_comparison_decision_skill is a skill published in the GitHub repository chuancyzhang/deepseek-cowork (18 stars, last pushed today), licensed Apache-2.0. It adds 66 tokens to every session and 1,344 once invoked, about $0.0003 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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