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 agentmods add skills/travisun/opptrix/financial-datanpx skills add Travisun/Opptrix --skill financial-datagit clone --depth 1 https://github.com/Travisun/OpptrixWrote 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/travisun/opptrix/financial-data)<a href="https://agentmods.dev/skills/travisun/opptrix/financial-data"><img src="https://agentmods.dev/badge/skills/travisun/opptrix/financial-data.svg" alt="Measured on agentmods" 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 | $0.00111 | $0.02290 |
| Opus 5 | $0.00056 | $0.01145 |
| Sonnet 5 | $0.00022 | $0.00458 |
| Haiku 4.5 | $0.00011 | $0.00229 |
Grade A, and why
financial-data 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.
How it starts
The opening of the file, as written. The whole thing — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
财务数据获取与交叉验证
本技能规范：每个关键财务数字须可核验；有第二源时交叉验证；估值倍数用精确十进制脚本算，禁止让模型凭印象口算 PE/PB。
何时使用 / 非目标
| 使用 | 不要用本技能 |
|---|---|
| 核对营收/净利/市值、双源差异、市值=股价×股本验算 | 只要口头「大概多少 PE」且拒绝取数 |
| 报告定稿前 15% 数据抽检准出/打回 | 完整三表预测模型 → @skill:financial-model |
| 交付「数据交叉验证表」网页 | 盈利质量深挖 → @skill:earnings-quality；可比倍数样本 → @skill:comps-analysis |
与「裸问模型算 PE」的边界（硬性）
- ❌ 用户问 PE/PB/市值时，禁止直接用训练记忆或口头估算输出「权威」数字。
- ✅ 先
get_instrument_quotes/snapshot+get_instrument_financials（或 indicators）取数，再opptrix_run跑verify-valuation/calc/verify-market-cap。 - 缺数据时诚实写「暂无该期 EPS」，可给带假设标注的示意公式，但不得伪装成已核验行情。
Opptrix 取数（主路径）
禁止教 Agent 以 scrapy/爬 macrotrends 等外网页面作为主路径。外网公开年报/披露站仅可作补充说明；主路径一律 Opptrix 工具。
| 维度 | 工具 | 用途 |
|---|---|---|
| 财务摘要 | get_instrument_financials |
营收/利润/ROE/同比多期 |
| 资产负债表 | get_instrument_balance_sheet |
资产/负债/权益明细 |
| 现金流量表 | get_instrument_cash_flow |
经营/投资/筹资现金流 |
| 利润表 | get_instrument_income_statement |
营收/成本/费用明细 |
| 财务指标 | get_instrument_financial_indicators |
指标树（如报告期必填） |
| 快照 | get_instrument_snapshot |
聚合概况与关键字段 |
| K 线 | get_instrument_chart |
历史价（前复权口径用于历史序列） |
| 报价 | get_instrument_quotes |
最新价、涨跌幅（市值验算用现价） |
| 第二源 | get_instrument_notices / get_notice_content、get_instrument_institution_report，或用户提供的 panels 双源 |
交叉验证副来源 |
取数后写入 workspace，再跑脚本（脚本不联网）。
交叉验证规则（精髓）
误差率 = |来源1 − 来源2| / |来源1| × 100%
| 误差 | 处理 |
|---|---|
| ≤ 1% | 一致：取主源，标注双源 |
| 1% ~ 5% | 标记差异，注明两值与可能原因（GAAP/汇率/财年） |
| > 5% | 重大差异：须查公告/原始财报核实，不得直接采用 |
呈现示例：
收入：1,239 亿元 ✅
- Opptrix financials: 1,241
- notices / 用户 panel: 1,237
- 误差: 0.3%
常见差异原因：GAAP vs Non-GAAP、汇率时点、财年定义、合并口径、更新滞后。未上市公司仅一手来源时标记 [估计]，不强制交叉验证。原始财报/公告与工具冲突时，以披露原文为准并说明工具缺口。
股价与复权：历史涨幅/历史估值分位用前复权且同分析内不混用；当前市值/当前 PE 用现价 × 最新总股本（与复权无关）。增发回购后用 verify-market-cap（偏差 >5% 须核对股本/币种）。
脚本
| 脚本 | 作用 |
|---|---|
scripts/financial_rigor.py |
CLI：verify-market-cap / verify-valuation / cross-validate / benford / calc / three-scenario |
scripts/report_audit.py |
CLI：extract（抽检清单）/ verdict（准出/打回） |
scripts/run_rigor_json.py |
Agent 统一 JSON in/out（推荐） |
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago First seen · 150 lines · 111 tokens per session scan A 5d96f8632bc8
financial-data is a skill published in the GitHub repository Travisun/Opptrix (224 stars, last pushed 6d ago), licensed Apache-2.0. It adds 111 tokens to every session and 2,290 once invoked, about $0.0006 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.
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 /…
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。.
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。.
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。.
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。.
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。.