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 trading-sopgit 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/trading-sop)<a href="https://agentmods.dev/skills/fize/mmtickerlab/trading-sop"><img src="https://agentmods.dev/badge/skills/fize/mmtickerlab/trading-sop/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/trading-sop"><img src="https://agentmods.dev/badge/skills/fize/mmtickerlab/trading-sop.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 | $0.00178 | $0.02805 |
| Opus 5.5 | $0.00071 | $0.01122 |
| Sonnet 5.5 | $0.00036 | $0.00561 |
| Haiku 4.5 | $0.00018 | $0.00281 |
Grade B, and why
trading-sop scanned grade B with 1 finding 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 1mo 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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
为支持作为全局技能安装（如位于 `~/.gemini/config/skills/` 或 `~/.claude/skills/`）以及在任意用户工程目录下执行，**所有报告必须输出至用户当前工作空间（Current Workspace / CWD）下的 `report/` 目录中**，严禁将报告写在技能代码的安装目录内： How it starts
The opening of the file, as written. The whole thing — 204 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Trading SOP — 交易标准操作程序总编排
本技能是所有投研与决策技能的入口与调度层。它不生成任何原始数据，只负责：
- 识别用户意图 → 选择对应 SOP 链
- 按序/并行调用 已有技能（渐进式披露，各技能自行查阅其 SKILL.md）
- 汇总各技能输出 → 给出最终可操作建议
各子 Skill 也必须支持独立触发；本编排层不以既有报告代替数据核验。若必需数据缺失，先允许子 Skill 按自身契约补充并核验；补充后仍不可用时，保留现有规则，立即停止整条 SOP 链并输出阻断原因。
零虚构原则继承：若任一技能因数据缺失触发阻断，整条 SOP 链即刻终止，输出阻断通知，不继续生成后续分析。
第一步：意图识别与路由
根据用户输入判断目标 SOP 链。如意图不明确，先问清楚再执行。
| 用户意图关键词 / 场景 | 路由至 SOP 链 |
|---|---|
| 盘前、今日计划、开盘前怎么看 | → SOP-A（盘前段） |
| 午间复盘、盘中、上午怎么样 | → SOP-A（盘中段） |
| 收盘复盘、盘后、今天结果 | → SOP-A（盘后段） |
| 研究 XX 股票、深度分析、值不值得买 | → SOP-B：个股深度研究 |
| 首板、隔夜、今晚要不要留板 | → SOP-C：首板隔夜决策 |
| 模拟交易、买入、下单 | → SOP-C（执行段） |
当用户提供股票代码且没有指定 SOP 类型时，默认走 SOP-B（个股深度研究），同时询问是否需要结合当日大盘环境（叠加 SOP-A 盘前段）。
SOP-A：日内研究主线（盘前/盘中/盘后）
完整链路说明见 references/sop-a-daily.md。
盘前准备段
调用顺序（串行，前序失败则终止）：
1. market-intel → 获取隔夜外盘、宏观要闻、行业动态背景
2. plan-review → 执行盘前数据采集与计划报告生成
3. risk-guard → 标定当前大势 Regime（牛/结构性/震荡/熊）
4. [本技能] 汇总 → 输出操作建议（见下方输出规格）
执行时：先通知用户正在启动 SOP-A 盘前链，然后依次调用各技能。每个技能完成后简报结果再继续下一个，不要等全部完成后再一次性汇报。
盘中复盘段
调用顺序：
1. plan-review（盘中段）→ 基于午间快照复核盘前假设
2. risk-guard → 更新 Regime 判断（若大盘结构有变）
3. [本技能] 汇总 → 下午策略微调建议
盘后复盘段
调用顺序：
1. plan-review（盘后段）→ 收盘复盘报告
2. risk-guard → 次日 Regime 预判
3. market-intel → 检索今日重要公告与明日催化线索
4. [本技能] 汇总 → 明日操作方向建议
SOP-B：个股深度研究主线
完整链路说明见 references/sop-b-stock.md。
前置条件：用户必须提供标的代码或名称。
并行阶段（Phase 1）— 同时启动 3 个 Subagent：
├── ticker-pipeline / fundamental_valuation → 基本面 + 估值
├── ticker-pipeline / market_heat → 筹码 + 资金热度 + 机构参与
└── ticker-pipeline / intel_news → 消息面 + 舆情
串行阶段（Phase 2）— 等待 Phase 1 全部完成：
├── industry-research → 所属行业景气度与赛道对比
└── asset-analysis → 综合技术面诊断与多模型估值验证
门控阶段（Phase 3）— VETO 门禁：
└── risk-guard / risk_guard_agent → 独立风控审查，有 VETO 权
[本技能] 综合裁决 → 输出最终评级与操作建议
若用户还想了解当日大盘环境，在 Phase 1 同时启动 market-intel 获取宏观背景，作为 intel_news 的补充输入。
What ships with it
13 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.
- .clawhubignore 26 B
- evals/evals.json 3.0 KB
- references/sop-a-daily.md 4.2 KB
- references/sop-b-stock.md 4.5 KB
- references/sop-c-firstboard.md 4.7 KB
- scripts/market_reader.py 15 KB runs code
- scripts/report_indexer.py 9.4 KB runs code
- scripts/server.py 6.1 KB runs code
- templates/sop_summary.md 1.2 KB
- tests/test_server_and_indexer.py 8.0 KB runs code
- tests/test_skill_contracts.py 1.8 KB runs code
- tests/test_versions.py 976 B runs code
- web/index.html 59 KB
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.
- 1mo ago Changed · +1 lines b51f10620840
- 1mo ago First seen · 203 lines · 178 tokens per session scan B 11b69de47c35
trading-sop is a skill published in the GitHub repository Fize/mmtickerlab (5 stars, last pushed 25d ago), licensed MIT. It adds 178 tokens to every session and 2,805 once invoked, about $0.0007 per session on Opus 5.5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-10.
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