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 vivy-yi/finance-skills --skill comparable-analysisgit clone --depth 1 https://github.com/vivy-yi/finance-skillsWrote 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/vivy-yi/finance-skills/comparable-analysis)<a href="https://agentmods.dev/skills/vivy-yi/finance-skills/comparable-analysis"><img src="https://agentmods.dev/badge/skills/vivy-yi/finance-skills/comparable-analysis/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/vivy-yi/finance-skills/comparable-analysis"><img src="https://agentmods.dev/badge/skills/vivy-yi/finance-skills/comparable-analysis.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 | $0.00084 | $0.02300 |
| Opus 5 | $0.00042 | $0.01150 |
| Sonnet 5 | $0.00017 | $0.00460 |
| Haiku 4.5 | $0.00008 | $0.00230 |
Grade A, and why
comparable-analysis 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 264 lines — stays where its author put it; the contents beside it link to each section on GitHub.
加载上下文
首次使用时: 读取 ../../CLAUDE.md 获取场景级配置(行业分类/倍数选择标准/调整项定义)。
/comparable-analysis — 可比公司分析
Examples
→ 示例:用户说"帮我找几家同行业上市公司作为可比,计算一下 EV/EBITDA 倍数",系统应调用本技能,执行可比公司筛选和估值倍数计算。
→ 示例:用户说"收购标的的 PB 看起来比同行低很多,这是机会还是陷阱",系统应调用本技能,分析 PB 差异的根本原因。
→ 示例:用户说"交易商给了一个 P/E 倍数,需要从财务角度评估是否合理",系统应调用本技能,执行 P/E 合理性分析。
第一步:可比公司选取
选取标准:
□ 行业标准:
→ 主营行业一致:[要求]
→ 收入结构相似度:>[X]%
□ 规模标准:
→ 收入规模:标的 [X]% - [X]% 范围内
→ 市值/估值规模:参照
□ 运营标准:
→ 商业模式相似:[是/否]
→ 地域分布相似:[是/否]
→ 发展阶段类似:[是/否]
选取结果:
□ 主要可比公司:[X] 家
| 公司名称 | 上市地 | 市值(亿) | 收入(亿) | EBITDA率 | 主要业务 |
|---------|--------|----------|----------|---------|---------|
| [公司A] | [A股] | [X] | [X] | [X]% | [描述] |
| [公司B] | [美股] | [X] | [X] | [X]% | [描述] |
| [公司C] | [港股] | [X] | [X] | [X]% | [描述] |
□ 排除公司:[名单] — 排除原因 [描述]
第二步:倍数计算
EV/EBITDA 倍数:
□ 计算公式:EV / EBITDA = (市值 + 净债务) / EBITDA
□ 可比公司倍数:
| 公司 | EV(亿) | EBITDA(亿) | 倍数 |
|------|---------|------------|------|
| [公司A] | [X] | [X] | [X]x |
| [公司B] | [X] | [X] | [X]x |
| [公司C] | [X] | [X] | [X]x |
□ 统计值:
→ 中位数:[X]x
→ 平均值:[X]x
→ 最低:[X]x | 最高:[X]x
P/E 倍数(如适用):
□ 计算公式:市值 / 净利润
□ 可比公司倍数:
| 公司 | 市值(亿) | 净利润(亿) | 倍数 |
|------|----------|------------|------|
| [公司A] | [X] | [X] | [X]x |
| [公司B] | [X] | [X] | [X]x |
□ 统计值:
→ 中位数:[X]x
→ 平均值:[X]x
P/S 倍数(如适用,用于亏损公司):
□ 可比公司倍数:
| 公司 | 市值(亿) | 收入(亿) | 倍数 |
|------|----------|----------|------|
| [公司A] | [X] | [X] | [X]x |
□ 统计值:中位数 [X]x
第三步:倍数调整
调整因素:
□ 流动性调整(非上市公司 → 上市公司基准):
→ 流动性折价:[X]%([X]% - [X]%)
→ 原因:[市场流动性差异]
□ 控制权调整:
→ 上市公司为少数股权价格,需加控制权溢价
→ 控制权溢价:[X]%([X]% - [X]%)
□ 规模调整:
→ 标的 vs 可比公司规模差异
→ 规模折价/溢价:[+/-X]%(原因:[描述])
□ 成长性调整:
→ 标的预期增速 vs 可比公司
→ 成长性溢价/折价:[+/-X]%(PEG 调整)
□ 盈利能力调整:
→ 标的 EBITDA 率 vs 可比公司
→ 调整:[+/-X]%([X]% vs [X]%)
调整后倍数:
□ 调整因子汇总:
→ 流动性:[+/-X]%
→ 控制权:[+/-X]%
→ 规模:[+/-X]%
→ 成长性:[+/-X]%
→ 盈利能力:[+/-X]%
→ 合计调整:[+/-X]%
□ 调整后中位数倍数:
→ 原中位数 [X]x × (1 + [X]%) = [X]x
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.
- 9d ago First seen · 264 lines · 84 tokens per session scan A 04c66aa7e183
comparable-analysis is a skill published in the GitHub repository vivy-yi/finance-skills (29 stars, last pushed 3mo ago), licensed MIT. It adds 84 tokens to every session and 2,300 once invoked, about $0.0004 per session on Opus 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 2026-09-03.
Other skills, from other repositories
wealth-structure
A framework for thinking about wealth through ownership, responsibility, leverage, and avoiding risks that could end your progress.
alpha-vantage
Access real-time and historical stock market data, forex rates, cryptocurrency prices, commodities, economic indicators, and 50+ technical indicators via the Alpha Vantage API. Use when fetching stock prices (OHLCV), company fundamentals (income statement, balance sheet, cash flow), earnings, options data, market…
hedgefundmonitor
Query the OFR (Office of Financial Research) Hedge Fund Monitor API for hedge fund data including SEC Form PF aggregated statistics, CFTC Traders in Financial Futures, FICC Sponsored Repo volumes, and FRB SCOOS dealer financing terms. Access time series data on hedge fund size, leverage, counterparties, liquidity…
edgartools
Python library for accessing, analyzing, and extracting data from SEC EDGAR filings. Use when working with SEC filings, financial statements (income statement, balance sheet, cash flow), XBRL financial data, insider trading (Form 4), institutional holdings (13F), company financials, annual/quarterly reports (10-K…
asc-ppp-pricing
Set territory-specific pricing for subscriptions and in-app purchases using current asc setup, pricing summary, price import, and price schedule commands. Use when adjusting prices by country or implementing localized PPP strategies.
fred-economic-data
Query FRED (Federal Reserve Economic Data) API for 800,000+ economic time series from 100+ sources. Access GDP, unemployment, inflation, interest rates, exchange rates, housing, and regional data. Use for macroeconomic analysis, financial research, policy studies, economic forecasting, and academic research requiring…