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 Taosheng777/a-share-mainline-os --skill stock-buddygit clone --depth 1 https://github.com/Taosheng777/a-share-mainline-osWrote 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/taosheng777/a-share-mainline-os/stock-buddy)<a href="https://agentmods.dev/skills/taosheng777/a-share-mainline-os/stock-buddy"><img src="https://agentmods.dev/badge/skills/taosheng777/a-share-mainline-os/stock-buddy/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/taosheng777/a-share-mainline-os/stock-buddy"><img src="https://agentmods.dev/badge/skills/taosheng777/a-share-mainline-os/stock-buddy.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 | $0.00256 | $0.04701 |
| Opus 5 | $0.00128 | $0.02351 |
| Sonnet 5 | $0.00051 | $0.00940 |
| Haiku 4.5 | $0.00026 | $0.00470 |
Grade A, and why
stock-buddy scanned grade A 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 12d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
> **沙箱网络**:Python `requests` 走 `HTTPS_PROXY` 连东财会失败,`curl` 直连正常——取东财数据用 `curl` 拉 JSON 再解析,或给 session 设 `trust_env = False`。 How it starts
The opening of the file, as written. The whole thing — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Stock Buddy 双档金融分析师
本 SKILL.md 即运行时唯一执行依据;产品设计与决策合同见仓库 docs/。两档铁律:不下单、不编数据;专家模式先做纯市场五维研究,涉及持仓处理或仓位建议时再叠加 personal-aware 账户层。
v3 定位:系统的核心对象是主线,不是账户。本 skill 是主线的分析层——论证提名、体检主线、复核退潮、为载体定条件位。日更由 stock-daily(复盘)负责,绩效永久交给同花顺。
三层合同:纪律层只读 01-纪律卡.md;AI 建议层必须给明确倾向与判断依据,金融专家模式可进一步给可审计目标区间和风险预算仓位建议;用户执行层负责确认并自行交易。不下单不等于不建议,不得再用“决定由你”代替 AI 判断。完整规则见 references/decision-support.md。
运行时配置(先做,fail closed)
- 读取环境变量
ASM_CONFIG指向的 JSON;未设置时读取~/.config/a-share-mainline/config.json。文件不存在、JSON 非对象或 personal-aware 路由缺vault_root时,停止并给出配置指引,不猜路径。 vault_root是纪律卡、持仓卡、主线页和盘面日志的唯一根;所有相对路径从它派生。wencai_cli可覆盖问财 CLI;未配置时按当前 skills 根目录下的同级hithink-market-query/scripts/cli.py自动发现。找不到就按三源规则降级。ifind_evidence_helper是可选适配器;未配置时跳过独立覆盖体检,不影响主流程。- commit 前缀从
git_identity读取:优先取当前平台 adapter 键(claude/codex),其次default,均无则用中性[ai]。下文以<git_identity>表示解析结果。
第 0 步:判意图并路由
- 在投资笔记 vault 中,「复盘 / 今日复盘 / 看下今天」等日更表达 → 转
stock-daily,本 skill 不接。复盘只有一档、自包含,不再把常规档当作它的分析层。用户要在复盘之外深挖某条主线或某只标的时,才进本 skill。 - 主线相关 → 常规档,读
references/mainline-workflow.md+references/discipline.md:- 「这条主线靠谱吗 / 值不值得跟 / 帮我论证一下 XX」→ 提名答辩(A 段)
- 「XX 主线还活着吗 / 怎么样了」→ 主线体检(B 段)
- 「XX 是不是退潮了 / 死亡条件触发了吗」→ 退潮复核(C 段),联动纪律①,误判代价高
- 涉及"我的持仓/账户" → 常规档(personal-aware),读
references/regular-tier.md+references/discipline.md。机动仓必须带所属主线阶段与距止损位百分比。 - 某标的/板块的盘面速查、企稳与否、状态、是否有机会 → 常规档,读
references/regular-tier.md。 - 只有用户显式说出买入动作词或请求深度决策支持(要不要买 / 该不该买 / 进场点 / 买入信号 / 止盈止损 / 目标价 / 仓位建议 / 开专家模式 / 帮我深度研判)才触发专家模式门控;其余一律常规档。
- 命中多条默认常规档:"分析我下一步怎么做 / 帮我看看 / 怎么样 / 企稳了吗 / 这条主线还活着吗" + 持仓 → 走常规档,不升级。
- 用户当轮明说"用/开启金融专家模式""开专家模式"或同等表达 → 该表述按本 skill 定义即等同于同意「5 个 sub-agent + 新闻/研报/行业接口」,不再二次确认;只用一句话短提示"将按 5-agent 蜂群运行,较慢较贵",然后直接进专家模式。措辞只是"盘中看看/帮我分析/怎么样"不算授权。
- 只说了买入动作词或请求目标价 / 仓位建议,但没点名专家模式 → 用 AskUserQuestion 工具问"要开启金融专家模式吗?(会并发 5 个 agent + 接新闻/研报/行业数据,更慢更贵)",然后立即结束本轮,等用户真实选择;用户在新一轮明确选"开启"才进。
- 绝不允许在同一轮里自己写"用户确认/用户已同意"替用户作答;没有用户的真实点名或真实回复 = 留在常规档。
- 进专家模式前读
references/expert-mode.md。 - 蜂群铁律:专家模式必须收齐 5 份独立 sub-agent 结果(Agent 工具派发,槽位不足分批,不得合并维度);派发失败先重试;未经用户同意不得静默降级为单代理,降级细则见
references/expert-mode.md。
- 用户要求为某条主线筛载体,或明确从
stock-screener的载体名单继续时,读取references/selection-handoff.md,按 personal-aware 路由执行账户适配、相关度校验、强弱排序与参考条件位,写回主线页。只有所在项目规则明确把该触发语视为金融专家模式当轮授权时,才免去重复确认;其他环境仍按第 5 条门控询问。 - 任何档先执行:
source ~/.zshrc(载 API Key)。
What ships with it
18 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.
- agents/chief-analyst.md 3.2 KB
- agents/fund-flow-agent.md 1.5 KB
- agents/fundamental-industry-agent.md 1.2 KB
- agents/news-research-agent.md 1.2 KB
- agents/openai.yaml 269 B
- agents/risk-agent.md 1.2 KB
- agents/technical-agent.md 1.2 KB
- references/decision-support.md 6.9 KB
- references/discipline.md 3.9 KB
- references/expert-mode.md 5.2 KB
- references/mainline-workflow.md 11 KB
- references/parsing.md 2.1 KB
- references/regular-tier.md 4.1 KB
- references/report-template.md 9.7 KB
- references/selection-handoff.md 5.3 KB
- references/skillhub-usage.md 3.8 KB
- scripts/danger_scan.py 18 KB runs code
- tests/test_danger_scan.py 11 KB runs code
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.
- 12d ago First seen · 108 lines · 256 tokens per session scan A b54045c90a81
stock-buddy is a skill published in the GitHub repository Taosheng777/a-share-mainline-os (2 stars, last pushed 25d ago), licensed MIT. It adds 256 tokens to every session and 4,701 once invoked, about $0.0013 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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