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 AndrewNgGirl/SkillLens --skill stock-trading-analystgit clone --depth 1 https://github.com/AndrewNgGirl/SkillLensWrote 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/andrewnggirl/skilllens/stock-trading-analyst)<a href="https://agentmods.dev/skills/andrewnggirl/skilllens/stock-trading-analyst"><img src="https://agentmods.dev/badge/skills/andrewnggirl/skilllens/stock-trading-analyst/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/andrewnggirl/skilllens/stock-trading-analyst"><img src="https://agentmods.dev/badge/skills/andrewnggirl/skilllens/stock-trading-analyst.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 | $0.00070 | $0.02344 |
| Opus 5.5 | $0.00028 | $0.00938 |
| Sonnet 5.5 | $0.00014 | $0.00469 |
| Haiku 4.5 | $0.00007 | $0.00234 |
Grade A, and why
stock-trading-analyst 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 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.
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 — 214 lines — stays where its author put it; the contents beside it link to each section on GitHub.
stock-trading-analyst
When to use
Use this skill when the user provides A-share market data and asks for:
- 今日题材轮动、涨停归因、资金生态分析
- 短线候选股筛选、观察池复盘、交易计划风控检查
- 个股异动原因拆解、板块强弱比较、情绪周期研判
- "帮我看看这批股票哪个更值得观察"
Not suitable for:直接给出买入 / 卖出指令、承诺收益、代客理财、荐股收费、绕过投顾合规要求、处理内幕信息或未授权账户数据。
Target users
- 有基础交易经验、需要结构化复盘的 A 股短线投资者
- 金融自媒体 / 投教团队，用于把盘面数据转成可解释的复盘框架
- 证券研究助理，用于整理公开市场数据、生成观察清单初稿
- 量化或半自动交易团队，用于人工复核前的信号解释层
Estimated frequency: daily after market close, plus intraday review during high-volatility sessions.
Value proposition
Most generic LLM stock prompts jump directly to "看好 / 不看好" and ignore evidence quality, position risk, data freshness, and compliance boundaries. This skill focuses on decision support, not trading instruction:
- separates market facts, inferred signals, assumptions, and risks;
- scores signal confidence instead of pretending certainty;
- keeps high-risk outputs behind a human-review checklist;
- uses schema validation so reports can be compared across days;
- explicitly refuses return promises and direct personalized investment advice.
Expected value: reduce a 60-90 minute manual replay of limit-up themes, capital flow, turnover, and risk notes into a 15-25 minute structured review, while preserving human judgment.
Inputs
| Field | Type | Required | Notes |
|---|---|---|---|
market_date |
string | yes | Trading date, e.g. 2026-05-07 |
universe |
enum | yes | a_share, hk_stock, us_stock; MVP tuned for a_share |
rows |
array | yes | User-provided table rows; one row per stock or concept |
scenario |
enum | optional | theme_rotation, watchlist, risk_audit, education |
risk_profile |
enum | optional | conservative, balanced, aggressive; defaults to balanced |
holding_context |
object | optional | Positions, cost basis, or target watchlist; do not include account credentials |
Recommended row fields:
{
"code": "000001",
"name": "示例股份",
"concepts": ["AI应用", "金融科技"],
"price_change_pct": 7.2,
"turnover_rate": 18.5,
"volume_ratio": 2.6,
"net_inflow_cny": 125000000,
"limit_up_reason": "题材催化 + 资金回流",
"news": ["公告摘要或公开新闻链接"],
"data_source": "user_upload",
"timestamp": "2026-05-07T15:10:00+08:00"
}
What ships with it
7 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.
- 1mo ago First seen · 214 lines · 70 tokens per session scan A e19e93f926fe
stock-trading-analyst is a skill published in the GitHub repository AndrewNgGirl/SkillLens (44 stars, last pushed 5mo ago), licensed MIT. It adds 70 tokens to every session and 2,344 once invoked, about $0.0003 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 2026-09-03.
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