Results for “learning-log”

Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard, MLflow), and distributed training (DDP, FSDP, DeepSpeed) for scalable neural network training.

Log workouts, plan routines, track progress, and get intelligent coaching for any fitness level.

Record, search, and prune per-project learnings in .claude/learnings.jsonl — typed, confidence-scored, searchable across sessions

Implements a continual learning loop for AI coding agents using hooks, two-tier memory (global and local), and automatic pattern detection to persist and apply learnings across sessions.

debug-logging

Design badge and achievement systems for learning. TRIGGERS - Use when user needs help with badge-system related tasks.

Investigate a problem, log it to the debug changelog, cross-check past issues, and suggest a non-duplicate fix.

Manage project learnings.

当需要高效掌握新技能并将知识转化为实际成果，避免“纸上谈兵”时

Help a user learn a topic through adaptive tutoring, lesson planning, practice, retrieval checks, explanations, study guides, or exercises. Use when the user asks to learn, understand, practice, drill

Execute self-learning system that captures corrections during sessions and syncs them to CLAUDE.md. Use when discussing learnings, corrections, or when the user mentions remembering something. Trigger with phrases like "remember this", "don't forget", "use X not Y", or "actually...".

Diagnose your own behavior by reading the structured logs you leave behind — turns.jsonl, events.jsonl, chat_history.jsonl, scheduler.yaml. Use when something has gone wrong (a message didn't land, a scheduled job isn't firing, a communication pattern feels off), when you need to understand a pattern over many turns, or when cost / token usage needs auditing. Covers jq query recipes and points at the debugging-jobs / debugging-communication / debugging-drift companion guides for specific failure modes.

Manage project learnings.

Design badge and achievement systems for learning. TRIGGERS - Use when user needs help with badge-system related tasks.

Interactive project learning coach via interview-style Q&A. Reads codebase and docs, dynamically generates interview questions per knowledge domain and sub-topic, conducts up to 4 follow-up rounds, scores answers, provides learning guidance with code/doc references, and persists progress. 10 domains × 3-5 sub-topics = 45 knowledge points for comprehensive interview coverage. Use when user says '学习项目', '了解项目', '检验项目', '项目学习', '面试准备', 'learn project', 'study project', 'review project', 'interview prep', 'knowledge check', or wants to understand/master the project through guided Q&A.

Help a user learn a topic through adaptive tutoring, lesson planning, practice, retrieval checks, explanations, study guides, or exercises. Use when the user asks to learn, understand, practice, drill, review, study, or be tutored on something.

Help a user learn a topic through adaptive tutoring, lesson planning, practice, retrieval checks, explanations, study guides, or exercises. Use when the user asks to learn, understand, practice, drill, review, study, or be tutored on something.

Converting repository changes into detailed learning documents. Use when turning diffs into teaching materials, recording design decisions, or creating onboarding materials for new members.

Interactive project learning coach via interview-style Q&A. Reads codebase and docs, dynamically generates interview questions per knowledge domain and sub-topic, conducts up to 4 follow-up rounds, scores answers, provides learning guidance with code/doc references, and persists progress. 10 domains × 3-5 sub-topics = 45 knowledge points for comprehensive interview coverage. Use when user says '学习项目', '了解项目', '检验项目', '项目学习', '面试准备', 'learn project', 'study project', 'review project', 'interview prep', 'knowledge check', or wants to understand/master the project through guided Q&A.

Recursive self-improving holon λ(ο,Κ,Σ).τ' for knowledge compounding and schema evolution. USE WHEN learning, improving, optimizing, assessing, reflecting, debugging, synthesizing, or refining—whether human, AI, or organizational. Triggers on /learn, /compound, /improve, /refine, /optimize, /assess, /reflect, "lessons learned", "best practices", "continuous improvement". Preserves Κ-monotonicity, η≥4, homoiconicity.

Build ontology logs (ologs) from problem descriptions using categorical foundations. Use when designing problem taxonomies, classifying tasks for routing, building knowledge libraries, establishing formal analogies between domains via functor search, or translating between natural language and database schemas. NOT for OWL/RDF ontology work, query tuning, or graph modeling without functional-arrow discipline.

Manage project learnings. Review, search, prune, and export what gstack has learned across sessions. Use when asked to "what have we learned", "show learnings", "prune stale learnings", or "export learnings". Proactively suggest when the user asks about past patterns or wonders "didn't we fix this before?"

Standards for structured logging and observability in Golang. Use when adding structured logging or tracing to Go services.

Analyze recent code changes via git history and extract software engineering lessons. Use when the user asks 'what is the lesson here?', 'what can I learn from this?', 'engineering takeaway', 'what did I just learn?', 'reflect on this code', or wants to extract principles from recent work.

Automatically evaluates Claude Code sessions to extract reusable patterns and save them as learned skills.

Automatically extract reusable patterns from Claude Code sessions and save them as learned skills for future use.

当需要快速掌握一门新技能或知识领域，且希望通过实践而非单纯理论学习时

Help a user learn a topic through adaptive tutoring, lesson planning, practice, retrieval checks, explanations, study guides, or exercises. Use when the user asks to learn, understand, practice, drill, review, study, or be tutored on something.

Manage project learnings.

Use when analyzing patterns across multiple incidents, bugs, failures, or successes to extract organizational learning. This skill provides procedures for synthesizing individual experiences into actionable lessons that improve team-wide practices.

Help a user learn a topic through adaptive tutoring, lesson planning, practice, retrieval checks, explanations, study guides, or exercises. Use when the user asks to learn, understand, practice, drill, review, study, or be tutored on something.

当需要深化对某个主题的理解、检验知识掌握程度或克服“冒名顶替综合征”时

Design reading plans with retention strategies. TRIGGERS - Use when user needs help with reading-plan related tasks.

Turns any long-running domain (business, relationships, health, career, learning, investing) into a local knowledge project with four layers, source tags, immutable snapshots, and a concept library that learns patterns over time.