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 Fize/mmtickerlab --skill asset-analysisgit clone --depth 1 https://github.com/Fize/mmtickerlabWrote 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/fize/mmtickerlab/asset-analysis)<a href="https://agentmods.dev/skills/fize/mmtickerlab/asset-analysis"><img src="https://agentmods.dev/badge/skills/fize/mmtickerlab/asset-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/fize/mmtickerlab/asset-analysis"><img src="https://agentmods.dev/badge/skills/fize/mmtickerlab/asset-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 | $0.00149 | $0.02993 |
| Opus 5 | $0.00075 | $0.01496 |
| Sonnet 5 | $0.00030 | $0.00599 |
| Haiku 4.5 | $0.00015 | $0.00299 |
Grade A, and why
asset-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 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.
How it starts
The opening of the file, as written. The whole thing — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Asset Analysis — 标的基本面与技术面量化分析
本技能作为投研流水线的第二步（标的深分析）。核心原则：基本面定质地、多模型定市值、技术面定点位、大势定权值。
零虚构与数据真实性铁律（Zero-Fabrication Data Gate）
- 真实数据唯一原则：报告中引用的 OHLC 价格、成交量额、最新 EPS、净利润、净资产、营收及 20+ 项技术指标必须 100% 为真实数据。
- 多级真实数据获取路径：
- 第一优先：调用
market技能（参见market/SKILL.md）获取确定性行情、财务与技术面数据； - 第二优先：若港美股特定财报字段缺少或命令暂时不可用，必须使用
search_web/read_url_content/tencent-news/agent-browser检索官方财报或交易所权威数据。
- 第一优先：调用
- 缺失即阻断（Fail-Fast）：若通过上述所有途径均无法获取到标的的关键真实财务（EPS/净利润）或行情数据，必须立即终止研报生成，直接告知用户：“由于无法获取 [标的代码] 的真实财报/行情数据，研报已安全阻断，拒绝提供未经证实的伪分析”。绝对禁止凭空捏造 EPS 或假设虚构市值！
真实数据采集（调用 market 技能）
本技能作为投研深分析，所有底层量化事实统一依赖 market 技能提供。执行时遵循渐进式披露原则，直接查阅 market/SKILL.md 调用对应能力：
| 分析维度 | market 对应指令与能力 |
获取的关键真实字段 |
|---|---|---|
| 实时行情与市值 | quote 命令 |
最新价（close）、涨跌幅（pct_chg）、换手率、总市值、PE(TTM)、PB |
| 多周期 K 线历史 | kline 命令 |
日/周/月/分钟 K 线（默认 120 条前复权日线，支撑中长期趋势判断） |
| 确定性技术面诊断 | technical 命令 |
20+ 项指标（MA5/10/20/60/120/250、MACD、RSI_6/14、KDJ、布林带、ATR） |
| 真实财务三大表 | financials 命令 |
利润表（income：扣非 EPS、归母净利润、营业收入及同比增速）、资产负债表（balance_sheet：净资产、负债率、ROE）、现金流量表（cashflow：经营活动净现金流） |
| 筹码分布与资金流 | chips / stock-flow 命令 |
获利盘比例、平均成本、70%/90% 集中度及 1/3/5 日主力资金净流入 |
基本面 EPS 与多模型市值估值体系
必须基于真实财报基数，使用不少于 3 种主流估值模型对标的进行理论目标市值测算：
1. 核心每股收益（EPS）与盈利基数
- 基本每股收益 (Basic EPS)：从利润表直接提取最新季度/半年/年报数据；
- TTM 每股收益 (EPS_TTM)：滚动 12 个月累计 EPS，作为市盈率核算基准；
- 总股本与基准市值：当前总市值 = 当前股价 × 总股本。
2. 多模型目标市值测算方法
| 估值模型 | 适用企业类型 | 核心计算公式 | 关键假定依据 |
|---|---|---|---|
| PE 相对估值法 | 盈利稳定、商业模式成熟的企业（如白酒、家电、公用事业） | $\text{目标市值} = \text{净利润 (EPS} \times \text{总股本)} \times \text{合理 PE}$ | 参考行业历史 3/5 年估值中位数或同业头部对标 |
| PEG 成长估值法 | 高成长且业绩增速可预期的成长股（如消费电子、高端制造） | $\text{目标市值} = \text{净利润} \times (g \times 100 \times \text{基准 PEG})$ | 假定基准 PEG=1.0（合理），以净利润复合增速 $g$ 修正 PE |
| PB-ROE 资产估值法 | 周期性、重资产、金融地产及公用事业等依靠资产驱动的企业 | $\text{目标市值} = \text{归母净资产} \times \text{合理 PB}$ | 根据 ROE 水平测算合理 PB 溢价（$\text{合理 PB} \approx \text{ROE} / (\text{COE} - g)$） |
| PS 市销率法 | 处于高研发、高扩张期、微利或尚未实现大额盈利的新兴科技/SaaS/创新药 | $\text{目标市值} = \text{营业收入} \times \text{合理 PS}$ | 参考同类业务 SaaS 续约率或创新药商业化倍数 |
| 简化 DCF / 自由现金流折现 | 现金流充沛且资本开支稳定的成熟价值股 | $\text{内在价值} = \sum \frac{\text{FCF}_t}{(1+\text{WACC})^t} + \frac{\text{TV}}{(1+\text{WACC})^n}$ | 基于自由现金流、WACC（如 8%~10%）及永续增长率（2%~3%） |
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.
- today Changed · +5 lines · +75 tokens per session b9985d2fadef
- 4d ago First seen · 129 lines · 74 tokens per session scan A 6bb39e1b47eb
asset-analysis is a skill published in the GitHub repository Fize/mmtickerlab (5 stars, last pushed today), licensed MIT. It adds 149 tokens to every session and 2,993 once invoked, about $0.0007 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 2026-09-05.
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