Results for “memo”

Expert guidance for fast fine-tuning with Unsloth - 2-5x faster training, 50-80% less memory, LoRA/QLoRA optimization

Expert guidance for fast fine-tuning with Unsloth - 2-5x faster training, 50-80% less memory, LoRA/QLoRA optimization

Review Qt6 C++ code for correctness, memory ownership, and idiomatic use of QObject, signals/slots, and implicit sharing.

JVM performance profiling with Java Flight Recorder (JFR), jcmd, and GC analysis. Use for identifying bottlenecks and memory issues. USE WHEN: user mentions "Java profiling", "JFR", "JVM performance", asks about "Java Flight Recorder", "jcmd", "heap dump", "GC tuning", "thread dump", "Java memory leak" DO NOT USE FOR: Node.js/Python profiling - use respective skills instead

Surface relevant project memory at session start or on demand. Trigger: session start, 'recall', 'remember', 'what do you know', 'context', /recall

Create and maintain TeamMember entities — humans and named AI personas that participate in the project with persistent identity, personality, and tiered memory. Use when adding a new persistent team-member (human or named AI), managing the name pool, scaffolding memory trees, or exporting/importing a team-member bundle. Replaces the deprecated actor-profile skill (DEC-20260422_0233-SpryTulip).

Node.js performance profiling with V8 CPU profiler, heap analysis, and perf_hooks. Use for identifying bottlenecks and memory leaks. USE WHEN: user mentions "Node.js performance", "profiling", "memory leak", asks about "V8 profiler", "heap snapshot", "CPU profile", "perf_hooks", "event loop lag", "Node.js optimization" DO NOT USE FOR: Java/Python profiling - use respective skills instead

Redis in-memory data store. Covers data structures, caching, and pub/sub. Use for caching and real-time features. USE WHEN: user mentions "redis", "caching", "session storage", "rate limiting", "pub/sub", "sorted sets", "in-memory database", "cache invalidation" DO NOT USE FOR: relational data - use `postgresql` or `mysql` instead, document storage - use `mongodb` instead, full-text search - use `elasticsearch` instead

Foundational C programming patterns covering type system, memory management, pointers, arrays, preprocessor, compilation, concurrency (pthreads, mutexes, atomics), serialization (binary, JSON, struct packing), and testing (Unity, CMocka, Check). Complete 8/8 pillar coverage. Use when writing C code, understanding manual memory management, working with system-level programming, or needing guidance on which specialized C skill to use. This is the entry point for C development.

Guides optimization of Qdrant query latency by tuning segments, memory, quantization, and search parameters.

Transforms lessons learned into domain-organized memory instructions (global or workspace). Syntax: `/remember [>domain [scope]] lesson clue` where scope is `global` (default), `user`, `workspace`, or `ws`.

FREE — God-tier long-context memory for AI agents. Injects 500K-1M clean tokens, auto-summarizes with tone/intent preservation, compresses 14-turn history into 800 tokens.

FREE — God-tier long-context memory for AI agents. Injects 500K-1M clean tokens, auto-summarizes with tone/intent preservation, compresses 14-turn history into 800 tokens.

Multimodal proposal brief intake — turns text, audio, or video into a structured, completeness-checked brief.md. Use when the user pastes a client brief, drops a voice memo or call recording, shares a video brief, asks to 'intake a proposal', 'structure this brief', or starts a new proposal run. Triggers: 'intake this brief', 'transcribe this recording', 'structure the brief', 'new proposal from voice memo', 'parse this RFP brief'.

Secure Solana wallet generation using official Solana Labs libraries — Ed25519 keypairs, memory zeroization, vanity address generation, offline-only operation, and multi-language implementations (Rust, TypeScript, Bash).

FREE — God-tier long-context memory for AI agents. Injects 500K-1M clean tokens, auto-summarizes with tone/intent preservation, compresses 14-turn history into 800 tokens.

Write, append, or read desk journal entries. The journal is persistent memory — what survives session boundaries. A good entry has: what was done, current state, next step.

Compassionate bereavement support, memorial creation, grief education, and healing journey guidance. Specializes in understanding grief stages, creating meaningful tributes, and supporting the non-linear path of loss.

FREE — God-tier long-context memory for AI agents. Injects 500K-1M clean tokens, auto-summarizes with tone/intent preservation, compresses 14-turn history into 800 tokens.

Brainstorm 5 unique, memorable product names with rationale aligned to brand values and target audience. Use when naming a new product, rebranding, or exploring product name ideas.

Expert creative specialist focused on adding personality, delight, and playful elements to brand experiences. Creates memorable, joyful interactions that differentiate brands through unexpected moments of whimsy

Monitor system resources with htop and related tools. Use when a user asks to check CPU/memory usage, find resource-hungry processes, monitor server performance, or diagnose system bottlenecks.

Node.js runtime best practices. Covers event loop, async patterns, streams, worker threads, memory management, and production optimization. USE WHEN: user mentions "node.js", "event loop", "streams", "worker threads", asks about "process.nextTick", "memory leaks", "cluster mode", "async patterns" DO NOT USE FOR: Express/NestJS frameworks - use framework-specific skills DO NOT USE FOR: Language syntax - use `javascript` or `typescript` skills DO NOT USE FOR: Package management - use npm/pnpm/yarn skills

Craft messages that are understood, remembered, and drive action using the SUCCESs checklist (Simple, Unexpected, Concrete, Credible, Emotional, Stories). Use when the user mentions "make it memorable", "sticky messaging", "tagline", "value proposition", "why the message isnt landing", "knowledge curse", "surprise gap", or "concrete language". Also trigger when writing pitch decks, simplifying complex product explanations, or making presentations more compelling and memorable. For narrative brand frameworks, see storybrand-messaging. For viral sharing, see contagious.

Analyze core dumps, debug live processes, and investigate crashes, deadlocks, and memory issues in C/C++ programs using GDB with source code correlation.

Provides expert guidance on modern Rust development, covering async patterns, advanced type system features, and production-ready systems programming.

Search claude-mem's persistent cross-session memory database. Use when user asks "did we already solve this?", "how did we do X last time?", or needs work from previous sessions.

Build educational TypeScript vanity-address tooling for Pump.fun/Solana wallets with @solana/web3.js, async generators, event-loop yielding, prefix/suffix matching, batch search, and best-effort memory zeroization.

Foundational Carbon patterns covering memory safety, modern syntax, C++ interop, and Carbon idioms. Use when writing Carbon code or migrating from C++. This is the entry point for Carbon development.

Diagnose and fix SwiftUI performance issues like slow rendering, janky scrolling, and high CPU/memory usage through code review and profiling guidance.

Apply the Von Restorff Effect to make the most important element visually distinct from its surroundings, improving attention and recall.

Analyze auto-memory for promotion candidates, stale entries, consolidation opportunities, and health metrics. Use when the user runs /si:review or asks what has been learned and what should be promoted or pruned.

Use when context window is filling up, sessions are getting slow, or you need to preserve state across sessions. For context compression, state snapshots, search-first discipline, and cross-session memory management.

Hunt for Mimikatz execution using command-line patterns, LSASS access signatures, binary indicators, and in-memory detection of known modules.

KQL language expertise for writing correct, efficient Kusto Query Language queries. Covers syntax gotchas, join patterns, dynamic types, datetime pitfalls, regex patterns, serialization, memory management, result-size discipline, and advanced functions (geo, vector, graph).

Review L2 session facts and promote valuable ones to L1 Atomic Memory. Use at end of session or when L2 accumulates facts worth keeping permanently. Runs add-fact.sh for each promoted fact.