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shap

Open source alternatives to shap

24 open source AI Skills apps to use instead, best rated first.

Top picks

  1. G

    github-ops

    Launch

    github-ops is an agent skill from the ECC collection by affaan-m, listed on skills.sh. It manages a GitHub repository with a focus on community health, CI reliability and the experience of contributors. It covers triaging issues by classify

    Open source

  2. O

    opensource-pipeline

    Launch

    opensource-pipeline is an agent skill from the ECC collection by affaan-m, listed on skills.sh. It prepares a private project for safe public release through a three-stage pipeline. The fork stage strips secrets from a copy. The sanitise st

    Open source

  3. A

    andrej-karpathy-skills

    Launch

    andrej-karpathy-skills is a single CLAUDE.md file from the multica-ai project that is meant to improve how Claude Code behaves on coding tasks. It is derived from Andrej Karpathy's public observations about LLM coding pitfalls. The file dis

    Open source

  4. M

    microsoft/markitdown

    Launch

    markitdown-mcp is the MCP server package for MarkItDown, Microsoft's tool for converting many file formats to Markdown for language models. It is a lightweight server that runs over stdio, Streamable HTTP or SSE, and exposes one tool, conve

    Open source

  5. O

    od-contribute

    Launch

    od-contribute is an agent skill in the OpenDesign project that provides a guided, one-click contribution flow to the OpenDesign repository, written so that people without a coding background can send a real pull request. It is locked to the

    Open source

  6. G

    github-deep-research

    Launch

    github-deep-research is an agent skill from the DeerFlow project that researches a single GitHub repository in several rounds and writes a report in Markdown. It is for requests that need more than a README summary, such as a comprehensive

    Open source

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About shap

S

shap

Explain and audit machine-learning predictions with SHAP

shap is an agent skill for explaining and auditing machine-learning predictions with SHAP. It describes how a fitted model maps inputs to outputs. The skill works from the modern shap.Explanation interface, makes the explained output and the background distribution explicit, and checks every explanation before anyone interprets it. It covers choosing explainers and maskers, computing and validating feature attributions, and plotting them. It is aligned with SHAP 0.52.0, released on 28 May 2026, which requires Python 3.12 or newer. The maintained examples were checked on Python 3.12 with NumPy 2.5.3, pandas 3.0.6, scikit-learn 1.9.1 and matplotlib 3.11.2. Native tests cover several explainer types, and XGBoost 3.4.1 smoke checks cover raw, probability, loss and interaction outputs. The skill sets firm operating rules. It explains a fixed, evaluated model and does not use SHAP as a substitute for predictive validation. Explanations should use held-out rows, and background rows should come from an appropriate reference population.

View shapAll AI Skills apps
Price
Free
Made by
k-dense-ai
Category
AI Skills
Website
github.com/k-dense-ai/scientific-agent-skills/shap