Model interpretability and explainability
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Plugin model-explainability-tool in jar-reis/athenaeum. Commands read from the repo's manifest — 1 month ago.
Explaining Machine Learning ModelsThis skill enables Claude to provide interpretability and explainability for machine learning models. It is triggered when the user requests explanations for model predictions, insights into feature importance, or help understanding model behavior. The skill leverages techniques like SHAP and LIME t
/model-explainability-tool:explain-modelExecute AI/ML task with intelligent automation
Dialectic claim discipline for AI agents: scholastic vocabulary, peer-grill file-based reconciliation, runnable verifiers/falsifiers, multi-agent ratification, fleet-ratify N-agent attestation, permutation NxN fleet topology ratification. Synthesis: an unexamined claim does not exist.
10 skills
Open-source investment research terminal integration - equity analysis, crypto tracking, macro indicators, portfolio optimization, and AI-powered financial insights using OpenBB Platform
6 commands · 4 agents
Comprehensive operations manager for FairDB managed PostgreSQL service - SOPs, incident response, monitoring, and automation
6 commands · 3 agents
Comprehensive operations manager for FairDB managed PostgreSQL service - SOPs, incident response, monitoring, and automation
6 commands · 3 agents
Engineering lifecycle skills forked from Matt Pocock's framework: SDLC scaffolding (setup-matt-pocock-skills), test-driven development (tdd), plan-to-issues decomposition (to-issues), context-to-PRD (to-prd), issue triage state machine (triage), disciplined diagnosis (diagnose), architecture deepening (improve-codebase-architecture), and zoom-out perspective (zoom-out). Run setup-matt-pocock-skills first to configure your repo before using the others.
8 skills
Complete operations kit for FairDB PostgreSQL as a Service - VPS setup, PostgreSQL management, customer provisioning, monitoring, and backup automation
1 skill · 4 commands · 1 agent
AI-powered codebase understanding — analyze, visualize, and explain any project
9 skills · 10 agents · hooks
DataRobot skills for AI/ML workflows — model training, deployment, predictions, feature engineering, monitoring, explainability, data preparation, App Framework CI/CD, and external agent monitoring.
19 skills
DataRobot skills for AI/ML workflows — model training, deployment, predictions, feature engineering, monitoring, explainability, data preparation, App Framework CI/CD, and external agent monitoring.
19 skills
Run a faster, provable month-end close. Three deterministic stdlib scripts: a close calendar planner that orders tasks by dependency, finds the critical path and slack, maps WD+n deadlines to dates and blocks on missing owners, missing or self-review of key controls and a critical path past the target workday; a reconciliation matcher that matches GL to bank or sub-ledger by reference then amount and date, builds the proof, ages reconciling items and blocks on any unexplained difference or preparer-as-reviewer; and a flux analyzer that applies your materiality rule and refuses material fluctuations explained with boilerplate or without a quantified driver. Ships cs-close-controller agent, /cs-month-end-close and /cs-flux-review commands, 3 references citing COSO 2013 and PCAOB AS 2201 / AS 2305 / SAPA 11, and a reconciliation sign-off template.
1 skill · 2 commands · 1 agent
Code-rendered motion videos up to 20 minutes: showreels, product films, UI motion, kinetic type, logo stings and narrated explainers. Independent music/SFX sources, Gemini/MiniMax TTS from user scripts, voice-led timing and cached chapter builds.
1 skill
Neural network interpretability tools including TransformerLens, SAELens, NNSight, and pyvene. Use when analyzing model internals, finding circuits, or understanding how models compute.
98 skills
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