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 atorber/qmt-trading-skill --skill qmt-bridge-kline-backfillgit clone --depth 1 https://github.com/atorber/qmt-trading-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/atorber/qmt-trading-skill/qmt-bridge-kline-backfill)<a href="https://agentmods.dev/skills/atorber/qmt-trading-skill/qmt-bridge-kline-backfill"><img src="https://agentmods.dev/badge/skills/atorber/qmt-trading-skill/qmt-bridge-kline-backfill/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/atorber/qmt-trading-skill/qmt-bridge-kline-backfill"><img src="https://agentmods.dev/badge/skills/atorber/qmt-trading-skill/qmt-bridge-kline-backfill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00078 | $0.01079 |
| Opus 5 | $0.00039 | $0.00540 |
| Sonnet 5 | $0.00016 | $0.00216 |
| Haiku 4.5 | $0.00008 | $0.00108 |
Grade A, and why
qmt-bridge-kline-backfill 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
QMT Trading Skill · 近3日量能校验
实现状态：✅
index_turnover_recent.py·backfill_recent_index_kline.py
共享逻辑：_shared/market_turnover_util.py
目标
在执行复盘前，校验近 N 日（默认 3）两市成交额是否齐全：
- 上证指数：
000001.SH - 深市指数：
399106.SZ（tick 缺 amount 时回退399001.SZ）
官方推荐 vs 本项目策略
迅投知识库（指数数据）：
| 场景 | 官方 API | 本项目复盘热路径 |
|---|---|---|
| 当日成交额 | get_full_tick → amount |
✅ GET /api/market/full_tick |
| 历史指数日 K | download_history_data + get_market_data_ex |
❌ 禁用（易 BSON 崩溃） |
| 历史缺口 | 需本地已下载数据 | ✅ reports/market_turnover_daily.json 每日 tick 累积 |
复盘/校验默认不调用 download_batch、get_local_data、get_market_data_ex、get_market_data。
可选 --try-history：先 download_batch 指数日线，再 get_market_data 子进程补历史并写入缓存（QMT 异常时慎用）。
推荐补齐近 3 日缺口（历史缺失时）：
# 1. 下载指数日线（仅 3 只，勿全市场）
python -c "
from datetime import date, timedelta
import sys; sys.path.insert(0,'skills/_shared')
from common import load_env_files, make_client
import argparse
load_env_files()
c,_=make_client(argparse.Namespace(host='127.0.0.1',port=8080,api_key='test-auto',account_id=None),False)
e=date.today().strftime('%Y%m%d'); s=(date.today()-timedelta(days=12)).strftime('%Y%m%d')
print(c.download_batch(['000001.SH','399106.SZ','399001.SZ'], period='1d', start_time=s, end_time=e))
"
# 2. 读 amount 写入缓存并展示明细
python skills/qmt-bridge-kline-backfill/scripts/index_turnover_recent.py \
--host 127.0.0.1 --port 8080 --try-history
脚本
# 查看近3日上证+深证成交额明细（亿元）
python skills/qmt-bridge-kline-backfill/scripts/index_turnover_recent.py \
--host 127.0.0.1 --port 8080
# 查看近3日成交额明细；历史缺口加 --try-history
python skills/qmt-bridge-kline-backfill/scripts/index_turnover_recent.py \
--host 127.0.0.1 --port 8080
# 可选：尝试从本地 K 线补历史（慎用，优先用上一条）
python skills/qmt-bridge-kline-backfill/scripts/index_turnover_recent.py \
--try-history --host 127.0.0.1 --port 8080
# 兼容旧入口（同上逻辑）
python skills/qmt-bridge-kline-backfill/scripts/backfill_recent_index_kline.py --json
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.
- 11d ago First seen · 92 lines · 78 tokens per session scan A 664d0e4b3cf3
qmt-bridge-kline-backfill is a skill published in the GitHub repository atorber/qmt-trading-skill (22 stars, last pushed 28d ago), licensed MIT. It adds 78 tokens to every session and 1,079 once invoked, about $0.0004 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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