自動去重、整理記憶檔案，模擬 Claude Code 的 Auto Dream 機制。

>

memwal

Karpathy's LLM Wiki pattern, built for Claude Code. Long-term memory for Claude via Obsidian: captures URLs, PDFs, GitHub, YouTube and compiles them into a structured Obsidian vault with citations that grows smarter every session. Second brain, zettelkasten, and autonomous research assistant in one. Keywords: llm-wiki, obsidian-plugin, knowledge-base, compounding-knowledge, claude-code, pkm, llm-memory.

<!-- NavAIgate NotebookLM Skill — navaigate.dev -->

Configures Laravel Nightwatch data collection, sampling rates, filtering rules, and redaction policies. Use when setting up Nightwatch, managing data volume, protecting sensitive data (PII), or optimizing event collection for production workloads.

Analyze writing samples to create a comprehensive voice DNA profile. Use when the user wants to capture their unique writing voice, needs to create a voice profile for AI content, or is setting up a new writing system.

Detects performance bottlenecks in Godot projects including expensive _process functions, get_node() calls in loops, instantiations in _process, and provides optimization suggestions with Godot profiler integration

Fan-out search across all memory sources when context is unclear or vaguely referenced. Triggers on: 'from earlier', 'remember when', 'what we discussed', 'that thing with', 'the conversation about', 'did we ever', 'what happened with', 'you mentioned', 'we talked about', 'earlier today', 'last session', 'the other day', or any vague reference to past context that needs resolution before the agent can act.

Structured approach to improving performance through focused effort, feedback, and

Investigate the intended scope of a codebase topic through discussion with a human, propose a research-note outline, and only create a .memory-bank/research file after explicit human confirmation.

Complete mastery of essential modern web development libraries and dependencies. Cover Next.js, React, TypeScript, Tailwind CSS, Firebase, Zustand, redux-toolkit, react-hook-form, Zod, shadcn/ui, lucide-react, Stripe, and more. Learn setup, integration patterns, advanced usage, performance optimization, troubleshooting, common pitfalls, and version management. Includes quick reference guides, in-depth tutorials, complete examples for e-commerce and SaaS, configuration files, type definitions, error handling, and production patterns. Master how libraries work together and solve real-world challenges.

Premier setup d'un nouvel utilisateur BOS. Déclenché automatiquement quand `Core/Profile.md` est vide ou n'existe pas.

This skill should be used when defining a robust, type-safe, and async-compatible database schema for the Todo application using SQLModel, ensuring compatibility with Better Auth and optimized for PostgreSQL.

Prepare a MemoryLane release by updating the version and release notes, then creating and pushing the tagged release commit that triggers CI. Use when the user asks to release, ship, publish, bump version, or cut a stable or prerelease version.

>-

Profile app performance while browsing, collecting Web Vitals and React rerender data via react-scan. Orchestrates parallel profiler subagents via playwright-cli to capture navigation timing, long tasks, layout shifts, LCP, React commit counts, render bursts, and per-component render data. Use when profiling browsing performance, finding bottlenecks, diagnosing excessive rerenders, or auditing page performance.

Implements Geoffrey Huntley's Ralph Wiggum autonomous iteration technique for managing LLM context. Use when working on long-running tasks, when context is getting polluted, or when you need autonomous development with deliberate context rotation. Treats LLM context like memory - rotates to fresh context before pollution builds up, with state persisting in files and git.

Rust web development expert covering HTTP frameworks (axum, actix), REST API design, handler patterns, state management, middleware, database integration, and domain-driven architecture.

Pin and self-referential types expert covering Pin, Unpin, Future, async state machines, pinning projection, and memory stability guarantees.

Caching and distributed storage expert covering Redis, connection pools, TTL strategies, cache patterns (Cache-Aside, Write-Through), invalidation, and performance optimization.

Unsafe code and FFI expert covering raw pointers (*mut, *const), FFI patterns, transmute, union, #[repr(C)], SAFETY comments, soundness rules, and undefined behavior prevention.

Analyze and safely evolve World42 OriginCamera floating-origin behavior end-to-end. Use when requests mention OriginCamera, doublepos vs position, teleport/camera placement, camera speed/velocity metrics, world/render conversion bugs, or when editing camera integrations in src/core/camera/, src/core/control/, src/app/, src/systems/lod/, and render postprocess paths.

INVOKE THIS SKILL at the START of any LangChain/LangGraph/Deep Agents project, before writing any agent code. Determines which framework layer is right for the task: LangChain, LangGraph, Deep Agents, or a combination. Must be consulted before other agent skills.

Lossless LLM-optimized compression of source documents. Use when the user requests to 'distill documents' or 'create a distillate'.

>-

Coordinate BioETL multi-agent workflow across py-* profiles using the Codex-local orchestration map.

Configure GSD workflow preferences including model profiles and agent settings. Use when the user says 'settings', 'configure', 'change profile', or wants to adjust workflow parameters. (Codex adapter)

Use Moneta shared memory via MCP tools to recall project knowledge

>

Use this skill whenever the user wants durable context, cross-project memory, shared procedures, audit trails, Obsidian-backed knowledge, or a reusable operating layer across multiple agent sessions. Trigger aggressively on requests to remember decisions, save findings, reuse previous workflows, coordinate several agents, maintain shared organizational context, install or activate MAKOS, or avoid starting from scratch in each conversation.

>

>

hologres-query-optimizer

GitHub-based developer outreach. Find repos, enrich maintainer profiles, draft personalized emails, track contacts. Zero paid APIs.

Comprehensive system health monitoring for AI agents. Monitors disk usage, memory, processes, network connectivity, and service health.

>

Use the Moneta CLI to recall project knowledge and remember

Monitor your AI agent's performance, API health, error patterns, and trigger automatic recovery actions.

Optimize transaction costs and gas usage for AI agents. Track gas spending, find optimal transaction timing, and minimize fees across EVM chains.

Create custom espresso extraction profiles for Gaggimate-equipped machines (Gaggia Classic Pro, Gaggia Classic Evo, Rancilio Silvia). Use when designing pressure profiles, flow profiles, blooming profiles, lever simulation profiles, or helping with espresso extraction settings and troubleshooting. Also use when the user mentions Gaggimate, espresso profiles, pressure profiling, or extraction parameters.

Clean up storage, manage cache, and prevent disk space issues for AI agents.

>

AI-powered SEO content creation toolkit. Research keywords, write optimized articles, and publish to WordPress/Ghost.

Comprehensive techniques for acquiring, analyzing, and extracting artifacts from memory dumps for incident response and malware analysis.

Analyze MaxText training job performance using tgs_tagger, TraceLens, and IRLens. Use when the user asks to analyze a training run, profile traces, HLO IR, TGS metrics, GPU utilization, or mentions tag_tgs, TraceLens, IRLens, xplane, or performance analysis.

Breaks complex systems into atomic components, maps their relationships, and reconstructs them in optimized configurations to identify bottlenecks, critical failure points, and redesign opportunities. Use when dealing with complex systems that need simplification, identifying bottlenecks or critical failure points, redesigning architecture or processes for better performance, breaking down problems that feel overwhelming, analyzing dependencies to understand ripple effects, or when optimization requires understanding how parts interact.

Change the Routing Solution routing profiles/vehicle types. To be used as part of customize-main skill

Execute SymCLI to solve math equations, optimize tensor graphs, or analyze C# code for vulnerabilities. Turn your coding agent into an AI mathematician, SymbolicComputation.com