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Found 58 Skills
Start a new learning episode in the self-learning memory system with proper context. Use this skill when beginning a new task that should be tracked for learning from execution patterns.
Analyze gaps between implementation plans and actual codebase implementation for the Rust self-learning memory project
Use when starting work on a new or unfamiliar project, when encountering unexpected patterns, when user corrects your assumptions, or when explicitly invoked via /learn - auto-discovers and remembers project context through structured codebase analysis
Autonomous skill generator that learns new technologies from the web. Use when, users want to learn about a new library/framework/tool, need to create a skill for an unfamiliar technology, want to research and document a technology's usage patterns, or invoke with `/learn <topic>`. This skill uses web search and browser tools to discover, extract, and synthesize documentation into a reusable skill.
Capture a hard-won "golden path" from the current session as a reusable Agent Skill, so future sessions start already knowing it. Use it (1) right after non-trivial debugging, after working out a multi-step operational workflow, or after rediscovering project facts you didn't know up front — e.g. how to reach the dev/prod database, where credentials and env vars live, how to deploy, run migrations, or verify a change live; and (2) whenever the user says "remember this", "save this as a skill", "make a skill for this", "don't make me re-explain this next time", or otherwise wants a workflow preserved across sessions. Proactively recognize the moment even when unprompted: if a task took several attempts before it worked, used non-obvious tooling, or is likely to recur, harvest it without asking first. Delegates to a subagent when your tool supports one, or works inline, to extract the proven procedure into a new project-local or global skill.
Asks for user feedback after each task or cron job completion and runs a recursive learning flow. If output is good, asks what was good until 10 approvals; if needs improvement, asks why/how/what via multiple choice plus optional examples, uses web search and iterative thinking to resolve, and caps iterations by severity (slight 5, medium 10, severe 20). Keeps feedback non-intrusive. Use when completing discrete tasks or cron jobs for the user.
Create, restructure, and validate Claude Code skills following best practices. Handles directory structure, YAML frontmatter, progressive disclosure, credential management, self-learning with consolidation, and script organization. Use when creating new skills, restructuring existing skills, reviewing skills for quality, or asking about skill structure, patterns, or best practices.
Implement ReasoningBank adaptive learning with AgentDBs 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learning agents, optimizing decision-making, or implementing experience replay systems.
Quantum-resistant, self-learning version control for AI agents with ReasoningBank intelligence and multi-agent coordination
WeWrite Self-Learning Module: Learns user writing preferences from manual edits (playbook flywheel), builds a style library by importing sample essays, and learns typography themes from WeChat Official Account articles. Trigger keywords: Learn my edits, I made changes, learn from them, Import sample essay, Learn from this article, View sample library, Learn typography, Learn layout. Should not be triggered by generic phrases like "learn" or "summarize this article" — requires WeChat Official Account / WeWrite context.
Enables autonomous pattern recognition, storage, and retrieval at project level with self-learning capabilities for continuous improvement
Comprehensive async/tokio testing patterns for episodic memory operations. Use when writing tests for async functions, time-based operations, concurrent tasks, or tokio runtime management.