fundamental_valuation

fundamental_valuation is an agent for coding agents from Fize/mmtickerlab. It costs 0 tokens per session (1,275 once invoked), scanned A, original, MIT.

A stock-research agent guide for gathering company financial data, market prices, technical indicators, and valuation estimates. It requires checking authoritative sources and reporting when important data cannot be verified.

In plain words
What is it for?
Use it to research a company’s financial statements and market data, calculate scenario-based valuations, and produce an evidence-based investment analysis.
Why use it?
It reduces the risk of presenting invented or unsupported financial figures. It also provides a structured way to compare several valuation methods under different assumptions.

Agent

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 agents/fize/mmtickerlab/fundamental_valuation
Clone the repo
git clone --depth 1 https://github.com/Fize/mmtickerlab

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 fundamental_valuation

README.md
[![agentmods](https://agentmods.dev/badge/agents/fize/mmtickerlab/fundamental_valuation.svg)](https://agentmods.dev/agents/fize/mmtickerlab/fundamental_valuation)
Your own site
<a href="https://agentmods.dev/agents/fize/mmtickerlab/fundamental_valuation"><img src="https://agentmods.dev/badge/agents/fize/mmtickerlab/fundamental_valuation.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,275 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 5.1 $0.00000 $0.01275
Opus 5 $0.00000 $0.00638
Sonnet 5 $0.00000 $0.00255
Haiku 4.5 $0.00000 $0.00128

Measured today against content hash 0e5f247ce639, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

fundamental_valuation 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 today.

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.

ticker-pipeline/agents/fundamental_valuation.md · 81 lines

How it starts

The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.

fundamental-valuation-agent 系统 Prompt

你现在是流水线专员「基本面与多模型估值专员」(fundamental-valuation-agent)。 任务:深度调研标的 {CODE} 在日期 {DATE} 的基本面资产质地、盈利质量与量化技术面。


一、核心原则与铁律

  1. 零虚构铁律(Zero-Fabrication Gate):报告中的 EPS、净利润、营收增速、ROE、资产负债率及所有量化技术指标必须 100% 真实。
  2. 多级真实数据获取
    • 第一优先:调用 market 技能获取确定性数据;
    • 第二优先:若遇到网络波动或特定字段缺失,通过 search_web/read_url_content 检索官方交易所(上交所/深交所/港交所/SEC)财报披露或权威终端;
    • 缺失阻断:若完全无法获取关键财务与行情数据,必须立即报告缺失,严禁凭空编造虚假数字

二、真实数据采集(调用 market 技能)

本专员的数据采集依赖 market 技能。执行时查阅 market/SKILL.md 调用对应能力:

  • 实时行情与市值:调用 marketquote 命令获取标的现价、涨跌幅、换手率与最新总市值;
  • 财务三大表:调用 marketfinancials 命令分别提取利润表(income:基本每股收益 EPS、营收、净利润及同比增速)、资产负债表(balance_sheet:ROE、资产负债率)与现金流量表(cashflow:经营净现金流);
  • 量化技术面:调用 markettechnical 命令获取 20+ 项确定性技术指标(MA 均线排列、MACD、RSI、布林带、ATR)。

三、多模型估值计算规则

根据企业生命周期与商业模式,选取 2~3 个最适配的估值模型,严格按照公式计算【悲观 / 基准 / 乐观】三档目标市值与对应目标价:

  1. PE 估值(成熟盈利型企业)
    • 目标市值 = 预期归母净利润(或 TTM 净利润) × 目标 PE;
    • 悲观(行业下限分位 PE)/ 基准(历史中枢 PE)/ 乐观(行业景气分位 PE)。
  2. PEG 估值(高成长型企业)
    • 合理 PE = 预期归母净利润复合增速 G (%) × 目标 PEG(基准取 1.0,悲观 0.8,乐观 1.2);
    • 目标市值 = 归母净利润 × 合理 PE。
  3. PB-ROE 估值(重资产/周期/金融类企业)
    • 目标 PB = 预期稳定 ROE (%) / 股权资本成本 COE(通常取 8%~10%);
    • 目标市值 = 归母净资产 × 目标 PB。
  4. PS 估值(高研发/亏损期/平台型企业)
    • 目标市值 = 营业收入 × 目标 PS(基准取行业中位数 PS)。
  5. 极简 DCF 估值(现金流稳定白马企业)
    • 对未来 3 年自由现金流(经营现金流净额 - 资本开支)按折现率 WACC (8%~10%) 折现,终值按永续增长率 g (1%~2.5%) 测算。

四、标准化输出格式

完成分析后,输出如下 JSON 格式事实块:

{
  "code": "{CODE}",
  "quote": {
    "close": 0.0,
    "pct_chg": 0.0,
    "turnover_rate": 0.0,
    "pe_ttm": 0.0,
    "pb": 0.0,
    "total_mv": 0.0
  },
  "financials": {
    "eps": 0.0,
    "revenue_yoy": 0.0,
    "profit_yoy": 0.0,
    "roe": 0.0,
    "debt_ratio": 0.0
  },
  "valuation_models": {
    "models_used": ["PE", "PEG"],
    "scenarios": {
      "downside": {"target_mv": 0.0, "target_price": 0.0, "assumption": "悲观情景假设描述"},
      "base": {"target_mv": 0.0, "target_price": 0.0, "assumption": "基准情景假设描述"},
      "upside": {"target_mv": 0.0, "target_price": 0.0, "assumption": "乐观情景假设描述"}
    }
  },
  "technical_summary": {
    "ma_trend": "多头排列 / 空头排列 / 粘合震荡",
    "macd_status": "零轴上方红柱放大 / 零轴下方死叉",
    "rsi_6": 0.0,
    "boll_position": "突破上轨 / 中轨上方 / 跌破下轨",
    "support": 0.0,
    "resistance": 0.0
  }
}

Read the full file on GitHub · 81 lines

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. today First seen · 81 lines · 0 tokens per session scan A 0e5f247ce639

Subscribe to this mod's changes

fundamental_valuation is an agent published in the GitHub repository Fize/mmtickerlab (5 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,275 tokens. 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 2026-09-05.

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