comps-analysis

A comparable-company valuation workflow, also called trading comparables, that compares a company with similar businesses using measures such as price-to-earnings, price-to-book, price-to-sales, or enterprise-value multiples. It summarises the comparison and marks missing or unreliable data.

In plain words
What is it for?
Use it to build a peer group, collect market and financial data, calculate available valuation multiples, compare medians and percentiles, and produce a comparison page.
Why use it?
It helps show whether a company trades at a premium or discount to its peers without building a discounted-cash-flow valuation. It separates reported facts, chosen assumptions, and conclusions drawn from the comparison.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/travisun/opptrix/comps-analysis
Any agent
npx skills add Travisun/Opptrix --skill comps-analysis
Clone the repo
git clone --depth 1 https://github.com/Travisun/Opptrix

Made for: Claude Code, Codex.

Per session 100 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,280 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00100 $0.01280
Opus 5 $0.00050 $0.00640
Sonnet 5 $0.00020 $0.00256
Haiku 4.5 $0.00010 $0.00128

Measured 3d ago against content hash 0fecf6746c32, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

comps-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 3d 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.

packages/agent-skills/builtin/comps-analysis/SKILL.md · 71 lines

What it actually says

可比公司(Trading Comps)

何时使用

用户要对目标公司相对同业的交易倍数做估值对照(PE/PB/PS/EV 等可用项),而非完整 DCF 或估值球场汇总页。边界:不做 @skill:dcf-model 的现金流折现;不做 @skill:football-field 的多方法区间并排总览——本技能聚焦 Trading Comps 样本与倍数表

分析架构(投研方法)

  • 问题/假设:目标相对同业是溢价还是折价?驱动因素是增长、盈利质量还是情绪?
  • 证据清单:行业/板块成分、指数成分、批量快照、概况与财务、目标与样本现价
  • 多维交叉验证:业务相似度 vs 倍数离散;增长/利润率 vs 溢折价;剔除异常值前后结论是否稳健
  • 结论与不确定:中位数/分位为事实汇总;「应交易在 X 倍」为推断且须标假设
  • 风险与缺口:样本过少、跨市场口径、缺 EV/净利导致倍数不可比
  • 事实 | 假设 | 推断 必须分栏:报表与行情为事实;可比标准与剔除规则为假设;溢折价含义为推断

数据维度

维度 取数方向 缺失时
目标标的 search_instruments / ask_user 多候选先确认
行业/板块池 get_sector_listget_sector_constituents 改用指数或用户给定名单
指数对照 get_index_constituents 省略指数列
批量行情 batch_instrument_snapshots 逐只 get_instrument_snapshot 并注明慢路径
概况/业务 get_instrument_profile 仅用代码/名称做弱可比
财务/倍数输入 get_instrument_financials 缺关键科目则该倍数标「不可比」
交付 list_web_vendorcreate_web 用户只要口头要点时可跳过

步骤

  1. 确认目标与可比范围:行业、市值带、是否含海外;不清则 ask_user
  2. 构建样本池:板块/指数成分 → 去重 → 业务相似度初筛(概况)。
  3. 取数:批量快照 + 财务;计算可用倍数;标注口径与报告期。
  4. 汇总与交叉验证:中位数/分位、目标分位、异常值;事实/假设/推断分栏。
  5. 交付网页(默认)list_web_vendorcreate_web 完整 HTML(倍数表 + 可选本地 vendor 散点/箱线);已有则 read_web / update_web。完整规范见 @skill:create-web
  6. 数据完整度:标注 partial——样本不足或关键倍数缺失时诚实降级,禁止填假数。

网页报告建议目录

  1. 目标卡片与数据时效
  2. 可比标准与样本筛选规则(假设)
  3. 样本名单与业务相似度说明
  4. Trading Comps 倍数表(含中位数/分位)
  5. 目标相对同业溢折价(事实汇总 + 推断分栏)
  6. 敏感性:剔除异常值 / 换样本
  7. 风险、缺口与后续观察
  8. 免责声明(无买卖建议)

禁止

  • 荐股、目标价、仓位建议;编造未返回的倍数或样本
  • 禁止无交付就结束(默认须有 web 产物,除非用户明确只要口头要点)
  • 禁止把本页伪装成完整 DCF 或 football-field 总览
  • assumption / not-feasible(样本过少、口径不可比)须诚实降级并写明原因
  • 禁止假装「市场共识倍数」若工具未返回共识数据
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. 3d ago First seen · 71 lines · 100 tokens per session scan A 0fecf6746c32

Subscribe to this mod's changes

comps-analysis is a skill published in the GitHub repository Travisun/Opptrix (224 stars, last pushed 5d ago), licensed Apache-2.0. It adds 100 tokens to every session and 1,280 once invoked, about $0.0005 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 2026-08-30.

Related

Other skills, from other repositories

national-team-position

估计中国 A 股"国家队"(中央汇金)的宽基 ETF 持仓变动趋势——追踪上交所沪深300/上证50/中证500/中证1000/中证A500/科创50 的 ETF 份额变化,叠加各自指数走势,生成六合一总图与各指数单图。Estimates China's "national team" (Central Huijin) broad-base ETF positioning by tracking Shanghai Stock Exchange ETF share changes. Use when the user asks about 国家队持仓 / 国家队仓位 / 中央汇金持仓 / 国家队加仓 / 国家队减仓 /…

Xiaoyuan-Liu/national-team-position · 161 tokens

caijing-ipo-hk

财经·港股打新——完整打新顾问 + 发行体检。回答"这只港股新股怎么打、打多少、破发统计风险多大"。内置:可配置用户档案(券商/资金/风险偏好)、主流券商费率预设、申请档位与历史配售证据、绝对孖展金额、因子体检(保荐人/基石/定价四分位/结构/热度/情绪/18A/18C)、三档条件性方案与执行清单。含招股期与数据时效 gate;默认自用模式可给条件性申购建议,对客输出仍按 compliance-rendering 降级。触发:"分析这个新股""XX招股了""怎么打""打多少手""港股打新""孖展""暗盘";命令 /caijing:ipo-hk。.

nekopunch11/rodya-caijing-studio · 209 tokens

caijing-fundamental

财经·基本面——产出一份分析师级、全面、详细、前瞻、论点驱动的深度研究文档。对 A股/港股上市公司:立核心论点与分歧视角(市场信什么、我哪里不同),在 2–3 个决定命运的胜负手上量化钻透(带估算区间与置信度),十四段全面框架每段有真分析与子项,配三情景前瞻盈利、估值矩阵、多投资哲学对撞、Pre-Mortem 反偏见与长期跟踪清单。默认产出研报级 docx;客户合规版按需。触发:"全面分析XX""XX基本面怎么样""这公司质地如何";命令 /caijing:fundamental。.

nekopunch11/rodya-caijing-studio · 188 tokens

rodya-caijing-studio

财经内容台——面向个人投资者、研究人员与券商投顾/客户经理的 A股+港股专业研究和内容生产工具包。用于全面分析公司基本面、点评财报、判断估值位置、排查财务风险、梳理产业链、体检 A股/港股新股;所有使用者默认获得同一专业研究内核和研报级 docx,客户合规版按需生成,卡片/文案/PPT 按用户点名触发。稳定命令:/caijing:fundamental、/caijing:earnings、/caijing:valuation、/caijing:risk、/caijing:industry、/caijing:ipo-a、/caijing:ipo-hk。.

nekopunch11/rodya-caijing-studio · 171 tokens

caijing-earnings

财经·财报——只回答"这季财报行不行/财报前该看什么"。财报发布后的事件驱动快评:最新期核验 gate、同比环比速览、超预期三层基准判定(一致预期优先于公司指引,公司指引优先于历史季节性)、扣非与现金流含金量验证、前瞻指标(合同负债/订单/资本开支)、对投资逻辑支柱的增强/削弱/中性影响;财报发布前可做 earnings preview(关键指标、三情景、催化清单)。默认产出专业版财报点评 docx;客户版财报速览卡+文案按需。触发:"XX出财报了""点评XX年报/中报/季报""这季业绩怎么样""财报前看什么""业绩预览";命令 /caijing:earnings。.

nekopunch11/rodya-caijing-studio · 215 tokens

caijing-valuation

财经·估值——只回答"现在贵不贵"。估值锚按行业适配(周期股低PE陷阱/银行PB-ROE/亏损成长PS)、历史分位 band(纵向)、同业四分位对标(横向)、估值中枢有效性检查(价值陷阱提示)、反向 DCF 隐含预期(不给目标价)、三情景变量敏感性。默认产出专业版估值分析 docx;客户版分位 band 卡+文案按需。触发:"XX贵不贵""现在什么位置""估值怎么样""能不能买"(只答贵不贵);命令 /caijing:valuation。.

nekopunch11/rodya-caijing-studio · 161 tokens