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 ZICXR/A-Stock-Skills --skill screenergit clone --depth 1 https://github.com/ZICXR/A-Stock-SkillsWrote 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/zicxr/a-stock-skills/screener)<a href="https://agentmods.dev/skills/zicxr/a-stock-skills/screener"><img src="https://agentmods.dev/badge/skills/zicxr/a-stock-skills/screener/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/zicxr/a-stock-skills/screener"><img src="https://agentmods.dev/badge/skills/zicxr/a-stock-skills/screener.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 | $0.00115 | $0.00689 |
| Opus 5 | $0.00057 | $0.00345 |
| Sonnet 5 | $0.00023 | $0.00138 |
| Haiku 4.5 | $0.00012 | $0.00069 |
Grade A, and why
screener 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 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.
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.
What it actually says
A 股股票筛选器 Skill (统一版)
何时使用
- 用户需要技术信号筛选
- 用户需要自定义条件筛选
- 用户需要多条件 AND/OR 组合
- 用户需要保存常用策略
提供能力
- 内置信号: 12 种 (ma_cross/macd/above_ma/volume/rsi/kdj 等)
- 自定义条件: 11 字段 × 9 操作符
- AND/OR 组合
- 策略保存: YAML 文件复用
使用方式
# 内置信号
python main.py screen --signals "macd_golden,above_ma20" --mode and
# 自定义条件
python main.py screen --where "pe<20" --where "roe>15"
# 组合
python main.py screen --where "pe<20" --signals "above_ma20,volume_break"
# 内置策略
python main.py screen --strategy value
# 列出策略
python main.py list
Python API
from skills.05-quant.screener.main import screen
# 自定义 + 信号
result = screen(
conditions=[{"field": "pe", "op": "<", "value": 20}],
signals=["macd_golden", "above_ma20"],
mode="and",
top_n=30,
)
内置信号
ma_cross / macd_golden / macd_death / above_ma20 / above_ma60 /
volume_break / volume_shrink / rsi_oversold / rsi_overbought /
kdj_golden / new_high_60 / limit_up
字段
pe / pb / ps / total_mv / circ_mv / roe / pct_change /
turnover / volume_ratio / price / change_5d / change_20d
操作符
> < >= <= == != between(a,b) in not in
依赖
akshare>=1.12.0
pandas>=1.5.0
numpy>=1.22.0
pyyaml>=5.4.0
合并历史
本 Skill 由原 signal-screener + stock-screener-custom 合并而成, 节省 1 个 Skill。
What ships with it
2 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.
- 12d ago First seen · 82 lines · 115 tokens per session scan A 126e434154fc
screener is a skill published in the GitHub repository ZICXR/A-Stock-Skills (25 stars, last pushed 2mo ago), licensed MIT. It adds 115 tokens to every session and 689 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.
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