Results for “memory”

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

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.

Sync durable project or session knowledge into the available memory systems so future sessions have accurate context. Use when meaningful work is complete and the user wants the result remembered.

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.

Profile a target (script, process, GPU, memory, interconnect) using external tools and code instrumentation. Produces structured performance reports with actionable recommendations. Use when user says "profile", "benchmark", "bottleneck", or wants performance analysis.

Summarizes WeChat group chat highlights into a structured digest using the local wx-cli binary, with per-group history, user profiles, and privacy guardrails.

Apply Miller's Law and chunking strategies to group information into meaningful units, making interfaces easier to scan, understand, and recall.

Reviews CUDA, OpenMP, and OpenCL code for parallel correctness, covering data races, memory model violations, synchronization bugs, numerical precision issues, and API-specific pitfalls.

Proactive self-monitoring of infrastructure, services, and health. Tracks disk/memory/load, service health, cron job status, recent errors. Auto-fixes safe issues. Triggers on: health check, heartbeat, monitor status, service status, infrastructure check.

Adds PyTorch FSDP2 (fully_shard) to training scripts with correct init, sharding, mixed precision/offload config, and distributed checkpointing. Use when models exceed single-GPU memory or when you need DTensor-based sharding with DeviceMesh.

Adds PyTorch FSDP2 (fully_shard) to training scripts with correct init, sharding, mixed precision/offload config, and distributed checkpointing. Use when models exceed single-GPU memory or when you need DTensor-based sharding with DeviceMesh.

Identify, collect, and analyze ransomware attack artifacts to determine the variant, initial access vector, encryption scope, and recovery options.

Record durable project decisions with rationale, alternatives, assumptions, status, and revisit triggers. Load when the user says record this decision, we decided, decision log, why did we choose, revisit this later, or capture architectural/process rationale.

Turn a proven pattern or debugging solution into a standalone reusable skill with SKILL.md, reference docs, and examples. Use when the user runs /si:extract or asks to package a recurring solution from memory into a skill.

Validates agent configuration files for Skills, Hooks, MCP, Memory, and Plugins across Claude Code, Cursor, GitHub Copilot, and Codex CLI against 230 rules, with optional auto-fixing.

Complete WhatsApp management for OpenClaw agents: per-conversation memory (groups + DMs), unanswered message tracking, loop prevention, and multi-PA coordination. Use when: tracking conversation context, recalling past decisions, finding unanswered messages, or preventing echo/duplicate message loops.

Sovereign-grade safety OS for AI coding agents. 63 hooks, 2,025 skills, L1 memory, circuit breakers, and cross-engine enforcement — blocks rm -rf, force push, pipe-to-shell, and 40+ attack vectors before they reach your repo.

Use when converting completed work into durable knowledge. This skill provides a systematic process for extracting lessons learned, patterns, and insights from completed work and storing them in memory systems (PARA, Gigabrain, OpenStinger) for future reuse.

Write correct, efficient Kusto Query Language queries with coverage of syntax, joins, dynamic types, datetime pitfalls, regex, serialization, memory management, and advanced functions.

Extract Kerberos tickets from LSASS memory, inject them into an attacker session, and perform lateral movement to access remote systems as the impersonated user.

Writes, reviews, and debugs idiomatic Rust code with memory safety and zero-cost abstractions, covering ownership patterns, lifetimes, trait hierarchies, async/await with tokio, and error handling with Result/Option.

Power management and performance optimization for Zephyr RTOS. Covers system power states (Idle, Suspend, Off), device-level power management, residency hooks, and code/data relocation for speed efficiency. Trigger when optimizing battery life, reducing latency, or managing memory constraints.

Analyzes bootkit and rootkit malware that infects MBR, VBR, or UEFI firmware for pre-OS persistence, covering boot sector analysis, UEFI module inspection, and anti-rootkit detection.

Execute advanced evasion by injecting malicious code into the memory space of a legitimate, suspended process (Process Hollowing). This skill details techniques to bypass static and dynamic analysis by masking malicious activity behind trusted processes like svchost.exe or explorer.exe.

Analyzes Perfetto traces to find the root cause of latency, memory, or jank issues in Android apps. Use when the user provides a Perfetto trace file and asks any question, ongoing investigation, or open-ended request to analyze its contents.

Runs before every git commit on heleni-memory. Checks: no credentials in tracked files, no oversized files, valid SKILL.md frontmatter for any new/modified skill. Triggers: "commit", "before push", "validate repo", or auto-runs as a git pre-commit hook.