“machine learning”

Help a human learn or understand a topic, technical system, code change, error, agent output, or source material.

Vet a perf measurement (limiter, tuning, limits, errors, repeatability, relevance, and whether the work happened) before you report or act on it.

Find the mistakes agents keep repeating in this repo and make each one impossible.

Spawn N parallel candidates at the same task, pick a base, graft the strongest parts of the losers into it.

Find what a change could break somewhere else before it ships, beyond the diff, and prove the one fact it's safe because of by running real code instead of…

Use when the user asks to see what they learned this session, create a session summary, or visualize learning progress.

Entry point.

Restate the last message in plain human language, with no jargon.

[Beta] Cross-session analysis of accumulated .learnings/ files.

Builds and differentiates PennyLane quantum circuits, hybrid PyTorch or JAX models, molecular VQE and QAOA workflows.

Learn how XState owns a lifecycle while Effect owns its work, errors, and services.

Decision transparency, feedback collection, and debate invitations for AID methodology.

Scaffold, structure, and manage AI/ML projects that run on AzureML.

Agent Platform Model Registry Management.

Use when a design, root-cause, review, or implementation-strategy decision point has passed the always-on learning-mode gate and a ★ Predict question, reason…

Use privacy-safe local execution outcomes to improve future backend choices conservatively, after capability, safety, availability and task fallback filters.

Explain and control the stellar-build learning loop — the system that improves your skills from how you use them.

Inspect or explicitly mutate text-free local learning state for a profile.

Generates Python code using BigQuery DataFrames (BigFrames).

互动式主题学习助手，依赖知识库结构化学习任务并交互引导完成学习过程

Shared step of the marketing playbooks (make-static-ads, analyze-performance, email-lifecycle, write-outreach): saves a short brand rule or finding in the…

Create and update LEARNING.md project retrospectives.

Detect AI-generated deepfake audio used in voice phishing (vishing) by extracting spectral features (MFCC, spectral centroid, spectral contrast, zero-crossing…

Use when the user asks to enable, disable, or explain Learning Mode's runtime behavior, or wants to deepen learning from recorded insights.