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Train a market forecasting model v1.0.0

Use this resource to run forecasting model training on market data

New

  • 557 downloads
  • 159 likes
  • 115 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install market-model-training

With no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.

First time: connect the CLI with

npx --yes palatekit@latest login

The agent installs neural-trader if needed and trains the chosen model on a symbol. In version 2.8.11 the result carries a stub flag: no model was actually fitted, and the skill reports this rather than hiding it.

Mostly picked by

Updated November 2, 2026

Card for the “Train a market forecasting model” skill

Details

Generates with
Your agent's model
Licence
MIT

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What you get

  • SKILL.md: training command and accepted models
  • SKILL.md: caveat on the placeholder result in version 2.8.11

Good fit for

  • You are testing the output format of a training run
  • You are following neural-trader's move to a real fit

Not for

    Tags

    • model
    • forecast
    • LSTM
    • market

    About

    You say

    “Train an LSTM on this portfolio's symbol for fifty epochs.”

    Card for the “Train a market forecasting model” skill

    Skill published by ruvnet under the MIT license, delivered in its original version.

    Show more

    How to use it

    1. Install the skill in your agent's skills folder
    2. Ask your agent to run forecasting model training on market data
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE1.1 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • SKILL.md2.1 KB

    Origin and licence

    Listed unmodified

    Author
    ruvnet
    Source
    github.com/ruvnet/ruflo/tree/89b0cd02dd99ea1f63437fde6c05992ec53cc22b/plugins/ruflo-neural-trader/skills/trader-train
    Licence
    MIT

    Notice

    « trader-train » (ruvnet, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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