Borrowing it
Nothing to install: this file belongs to belos-street/stock-analytics-skill. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/belos-street/stock-analytics-skill/main/.agents/business/report-review/SKILL.mdgit clone --depth 1 https://github.com/belos-street/stock-analytics-skillWrote 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/belos-street/stock-analytics-skill/report-review)<a href="https://agentmods.dev/skills/belos-street/stock-analytics-skill/report-review"><img src="https://agentmods.dev/badge/skills/belos-street/stock-analytics-skill/report-review/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/belos-street/stock-analytics-skill/report-review"><img src="https://agentmods.dev/badge/skills/belos-street/stock-analytics-skill/report-review.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 | $0.00118 | $0.02718 |
| Opus 5.5 | $0.00047 | $0.01087 |
| Sonnet 5.5 | $0.00024 | $0.00544 |
| Haiku 4.5 | $0.00012 | $0.00272 |
Grade A, and why
report-review 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 11d 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 — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
报告多维度审查 Skill（业务技能）
定位
.agents/business/ 存放交付/生产类技能。本技能与 html-report 配对：
| 技能 | 职责 | 时机 |
|---|---|---|
html-report |
怎么把分析结果做成报告 | 生成时 |
report-review（本技能） |
报告审得对不对 | 生成后、交付前（自动触发） |
自动触发规则：任何报告（reports/**/*.md、reports/**/*.html、watchlist/**/*.md）生成或修改完毕后，必须自动调用本技能完成 review，向用户输出审查结论后才算交付完成。用户单独要求 "review / 审查 / 核对 / 校对" 某份报告时同样调用。
七个审查维度
按顺序执行，前 5 个维度必须实证核验（跑 CLI / 算数 / 读图表 JS），不允许只凭报告自述判断。
D1 · 行情与基础数据核验
- 报告中每个价格 / 涨跌幅 / 市值 / 规模逐项与本地 CLI 对账：
bun run main.ts -s sh603799 --pretty # 个股/ETF 现价、涨跌、市值 bun run main.ts -f 006493 --pretty # 基金净值 bun run main.ts --dividend sh603799 # 股息率 - 输出一张「报告值 vs 实测值」对照表，精确到报告披露的小数位。
D2 · 时间窗口与口径核验 ⭐ 最高频错误
同一只股票在不同时间窗口下的"最高价 / 回撤 / 分位"完全不同。 必须核实报告口径词与实际取数窗口一致：
| 报告用词 | 合法口径 | 核验方法 |
|---|---|---|
| "年内高点/年内最高" | 自然年至今 | --kline <code> --period monthly 找全年 max high |
| "90 日高点 / 8/14 以来" | 明确窗口 | --period weekly/daily 对应窗口 max high |
| "距高点回撤 -X%" | 写明是哪个高点 | (现价/该窗口最高价-1)×100 复算 |
| "PE 分位" | 必须写明区间 | 近 1 年 / 近 10 年 / 基日以来三者数值差异巨大，禁止混用 |
⚠️ 陷阱：只看近 2 个月 K 线会把"阶段高点"误当"年内高点"。凡报告出现"年内/今年/YTD"字样，必须用 monthly K 线验证。
接口降级：K 线接口 socket 故障时（--kline 连续失败），改用公开披露的收盘价/盘中价快照交叉验证（证券之星行情快报、每经、交易所），并在报告中标注口径与数据来源；不可因接口不可用而跳过核验。
复权口径：K 线接口通常为前复权，行情快报为不复权价，两者可差一个分红额（例：华友 1/26 盘中高点 82.17 不复权 / 81.67 前复权，差额即 2026-05 分红 0.5 元）。引用"高点/低点/回撤基准"时必须标注复权口径。
D3 · 计算自洽性
- 复算所有派生数字：持仓成本/市值/浮亏额/浮亏%/回本涨幅/仓位占比/PE/PB。
- 常用公式：回本涨幅 = 成本/现价 - 1；PE = 市值/净利润；PB = 市值/净资产。
- 交叉校验：正文、指标卡、图表 JS 三处同一数字必须一致。
D4 · 估值与财务口径
- PE 是静态（上年报）/ TTM / 年化 / 动态哪种口径？报告若并列多种口径，各自注释是否清晰？
- 周期股低 PE 警示：低 PE 常出现在盈利顶部，报告是否提示"便宜有便宜的原因"？
- 分位数数据标注来源与区间（见 D2）。
D5 · 图表与文本一致性
- 打开
assets/charts.js（或内联 JS），逐项核对 series 数据与正文数字。 - 检查坐标轴是否截断（
yAxis.min/max把关键数据裁掉会视觉误导，如 K 线图 min/max 未覆盖年内高点）。 - 检查数据窗口是否与正文口径一致（正文讲"年内"，图表只画 8/14 以来 = 口径错位）。
- 每个 chart 是否有
<figcaption>标题；引用参考线标注（如"年内高点 X"）是否与 D2 核验结果一致。
D6 · 逻辑客观性
- 多空平衡：看多理由与看空/证伪风险是否都呈现？是否只堆利好？
- 沉没成本：决策建议是否围绕"成本价/回本"展开？正确的框架是"今天这个价位还愿不愿意持有"。
- 目标位语义：反弹目标位 ≠ 回本位，是否明确标注避免误读？
- 窗口期一致：触发条件（如"财报前不动手"）与操作建议是否自洽。
- 静默假设：仓位占比、风险承受力等未给定的输入，是否以"若…则…"分支表达而非硬编码结论。
What ships with it
1 file 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.
- 11d ago First seen · 144 lines · 118 tokens per session scan A c8e058557b9b
report-review is a skill published in the GitHub repository belos-street/stock-analytics-skill (56 stars, last pushed 6d ago), licensed MIT. It adds 118 tokens to every session and 2,718 once invoked, about $0.0005 per session on Opus 5.5. 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 2026-10-16.
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