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LSTM时序预测/序列建模助手 · aifinlab | DecimalAI

ai mlby aifinlab

LSTM时序预测/序列建模助手

aifinlab/a-share-lstm-forecast

Source aifinlab/finclaw ↗License Apache-2.0

A股LSTM时序预测/序列建模。当用户说"LSTM"、"时序预测"、"序列模型"、"RNN预测"、"GRU"、"循环神经网络"、"LSTM预测股价"时触发。基于 cn-stock-data 获取数据，构建LSTM时序预测模型。支持 formal/brief 两种输出风格。

SkillScore88Maintained

Automatic

AI Engineer pack

Last verified 8/28/2026

What it changes

Passed 21 of 24 test cases with the skill, and 19 of 24 without it.

Without skill80%

With skill88%

Checks it passed that the model alone missed

Selects Adam as the optimization algorithm.
Specifies learning rate decay from 1e-3 down to 1e-4.
Specifies using the cn-stock-data skill for data acquisition.

and 1 more in the full report

3 fixed19 passed either way2 still failing1 broke

Pass-rate lift: +8 pp
Tokens: +19%
Agent turns: 0%
Response time: +1%

Model gemini-3.6-flashMeasured 8/28/2026v122 of 25 cases passed with skill · 24 comparable

Tokens, turns and time describe resource use, not a dollar price.

Use this skill

Save it into your project's skills folder. Claude Code picks it up in its next session.

curl -fsSL --create-dirs -o .claude/skills/aifinlab-a-share-lstm-forecast/SKILL.md https://app.decimal.ai/s/aifinlab-a-share-lstm-forecast/SKILL.md

Want it pinned and updatable? pip install "decimalai>=0.15", then decimalai skills add aifinlab-a-share-lstm-forecast, and start Claude Code with claude --plugin-dir "$(git rev-parse --show-toplevel)/.agents"

1 · One-time — install the CLI (docs ↗)

pip install "decimalai>=0.15"

2 · Get the skill — writes .agents/skills/aifinlab-a-share-lstm-forecast/ and pins it in .decimal/skills.lock

decimalai skills add aifinlab-a-share-lstm-forecast

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/aifinlab-a-share-lstm-forecast/SKILL.md https://app.decimal.ai/s/aifinlab-a-share-lstm-forecast/SKILL.md

Raw file: /s/aifinlab-a-share-lstm-forecast/SKILL.md ↗ · machine-readable summary at /s/aifinlab-a-share-lstm-forecast.json ↗

Safety checks: 3 of 3 passed

Code scan CleanIntent PassedContent Clean

See it in action

One of 3 test cases the skill fixed. Same model, same prompt, with and without the skill.

1 of 3

Prompt

要对紫金矿业（601899）建立包含宏观利率、汇率以及技术指标的多变量 LSTM 预测体系，在数据获取环节应当通过什么专门的数据技能模块来拉取日线 K 线与外部指标？

What was checked, without and with the skill
Checked	Without skill	With skill
Specifies using the cn-stock-data skill for data acquisition.	Missed	Passed

case-13 · gemini-3.6-flash · 8/28/2026 · answers are capped and redacted

What's inside

The instructions your model reads when the skill loads.

SKILL.md85 lines2 files

LSTM时序预测/序列建模助手

数据获取

通过 cn-stock-data skill 获取数据：

K线数据: 日线序列(至少3年)
技术指标: 预计算的技术特征
宏观数据: 利率/汇率等外部序列

分析工作流

Step 1: 序列数据准备

滑动窗口：过去N天数据预测未来M天
特征标准化：Z-score或MinMax归一化
序列长度选择：通常20-60个交易日
多变量输入：OHLCV+技术指标+外部变量

Step 2: LSTM模型构建

网络结构：1-3层LSTM + Dense输出层
隐藏单元数：64-256，视数据量调整
Dropout：0.2-0.5防止过拟合
变体选择：LSTM/GRU/Bi-LSTM/Attention-LSTM

Step 3: 训练策略

损失函数：MSE(回归)/CrossEntropy(分类)
优化器：Adam，学习率1e-3→1e-4衰减
Early Stopping：验证集loss不降则停止
时序分割：严格按时间划分训练/验证/测试

Step 4: 预测与应用

点预测：未来1-5日收益率/价格
区间预测：预测值±置信区间
方向预测：涨跌概率输出
集成预测：多个LSTM模型投票/平均

Step 5: 输出报告

输出格式

formal 风格（研报级）

Track record

Benchmark

21 / 24

test cases passed, vs 19 / 24 without

Adoption

Users: 0
Times used: 0

Safety and source details

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 8/3/2026

View 15 scanner checks

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

aifinlab / finclaw

skills/a-share-lstm-forecast/SKILL.md

View on GitHub ↗

License Apache-2.0Imported 8/3/2026Version v1Bundled 1 file

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See it in action

What's inside

LSTM时序预测/序列建模助手

数据获取

分析工作流

Step 1: 序列数据准备

Step 2: LSTM模型构建

Step 3: 训练策略

Step 4: 预测与应用

Step 5: 输出报告

输出格式

formal 风格（研报级）

Track record

Benchmark

Adoption

SkillSafety

Source

Other skills for the same job

Related skills