shap

21.8k

davila7

Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias or fairness, comparing models, or implementing explainable AI. Works with tree-based models (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), linear models, and any black-box model.

shap

10.8k

K-Dense-AI

Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias or fairness, comparing models, or implementing explainable AI. Works with tree-based models (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), linear models, and any black-box model.

jb-terminal-wrapper

1.8k

openclaw

Terminal wrapper pattern for extending JBMultiTerminal functionality. Use when: (1) need dynamic splits at pay time, (2) revnet can't modify ruleset data hooks, (3) want atomic pay + distribute operations, (4) need to intercept/redirect tokens before delivery, (5) implementing pay-time configuration, (6) cash out + bridge/swap in one tx, (7) cash out + stake redeemed funds. Covers IJBTerminal implementation, _acceptFunds pattern from JBSwapTerminalRegistry, beneficiary manipulation for both pay and cash out flows, and the critical mental model that wrappers are additive (not restrictive).

additive-manufacturing

376

a5c-ai

Skill for additive manufacturing process selection, design optimization, and build preparation

API Schema Evolution Testing

71

PramodDutta

Testing API schema evolution patterns including additive changes, field deprecation, type widening, and backward-compatible migration strategies.

animation-systems

29

omer-metin

Expert in real-time game animation systems including skeletal animation, blend trees, state machines, inverse kinematics, root motion, procedural animation, and animation retargeting. Specializes in creating fluid, responsive character animation that balances visual quality with performance constraints. Use when animation system, state machine, blend tree, skeletal animation, inverse kinematics, IK system, root motion, animation blending, character animation, animator controller, motion matching, animation retargeting, foot IK, look-at IK, aim offset, animation montage, animation notify, additive animation, animation layers, procedural animation, animation, game-dev, character, state-machine, Unity, Unreal, Godot, skeletal, rigging, or motion are mentioned.

shap

26

lifangda

Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias or fairness, comparing models, or implementing explainable AI. Works with tree-based models (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), linear models, and any black-box model.

shap

15

oimiragieo

Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias or fairness, comparing models, or implementing explainable AI. Works with tree-based models (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), linear models, and any black-box model.

interactive-requirements-gathering

15

Oimiragieo Agent Studio Interactive Requirements Gathering

Structured interactive questionnaire framework for gathering requirements from users. Uses A/B/C/D/E multiple choice patterns with additive vs exclusive question classification.

sync-permissions

3

flonat

Sync global permissions into the current project and verify skills & agents symlinks. Additive merge — never removes existing project permissions.

shap

1

iamseungpil

Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias or fairness, comparing models, or implementing explainable AI. Works with tree-based models (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), linear models, and any black-box model.

fix

ordinary9843

Reviews any Claude Code artifact (SKILL.md, agent .md, hooks.json, plugin.json, marketplace.json, CLAUDE.md), then automatically generates an improved version targeting the highest-impact issues. Shows a before/after diff and asks for confirmation before writing. Follows the additive-only principle: never removes existing content. Auto-detects the file type from the path. Use when the user asks to "fix", "improve", "auto-fix", "enhance", "optimise", "rewrite", or "make better" any Claude Code file — or when a review score is below 80 and the user wants changes applied automatically.

SHAP

reikiplanet

Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias or fairness, comparing models, or implementing explainable AI. Works with tree-based models (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), linear models, and any black-box model.