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Explaining model predictions v1.0.0

Use this resource to explain the predictions of a machine learning model

New

  • 498 downloads
  • 116 likes
  • 178 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install model-prediction-explainability

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 picks an explanation technique (SHAP, LIME or feature importance) based on the question, then summarises what drives each prediction. The skill provides an HTML template and a stylesheet for the output. You get an explanation a non-specialist can read.

Mostly picked by

Updated November 2, 2026

Card for the “Explaining model predictions” skill

Details

Works in
Install guides
Generates with
Your agent's model
Licence
MIT

Similar resources

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What you get

  • SKILL.md: technique selection method and examples
  • assets/explanation_template.html: HTML output template
  • assets/visualization_styles.css: output styles

Good fit for

  • A customer asks why the model declined their application
  • You must check that a model does not rely on a sensitive variable

Not for

    Tags

    • explainability
    • shap
    • lime
    • model

    About

    You say

    “Explain why the model declined this loan application, listing the main factors.”

    Card for the “Explaining model predictions” skill

    Skill published by Jeremy Longshore <jeremy@intentsolutions.io> 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 explain the predictions of a machine learning model
    3. Review and adjust the result

    Content preview

    Files

    • assets/example_explanation.json3.6 KB
    • assets/explanation_template.html4 KB
    • assets/README.md0.4 KB
    • assets/visualization_styles.css2.6 KB
    • LICENSE1.1 KB
    • NOTICE-PALATEKIT.md0.6 KB
    • references/README.md0.1 KB
    • scripts/README.md0.4 KB
    • SKILL.md4.2 KB

    Origin and licence

    Listed unmodified

    Author
    Jeremy Longshore <jeremy@intentsolutions.io>
    Source
    github.com/jeremylongshore/tons-of-skills-marketplace/tree/ab85a061f7bcc039dac13ee193de7a4cd4388571/skills/.curated/explaining-machine-learning-models
    Licence
    MIT

    Notice

    « explaining-machine-learning-models » (Jeremy Longshore <jeremy@intentsolutions.io>, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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