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Found 130 Skills
Letta framework for building stateful AI agents with long-term memory. Use for AI agent development, memory management, tool integration, and multi-agent systems.
Add memories, learnings and context to OpenViking, aka. ov. Use when saving insights in chat. Trigger this tool when 1. sees keyword "ovm"; 2. is explicitly requested memorizing e.g. "remember ..." 3. identifies valuable memory worth adding
Nim 2.x: macros, templates, compile-time, memory ARC/ORC, FFI, Nimble, systems programming
Write the daily memory log entry. Use at end of day to record what happened.
nginx C module development guidelines based on the official nginx development guide. This skill should be used when writing, reviewing, or refactoring nginx C modules to ensure correct memory management, request lifecycle handling, and event-driven patterns. Triggers on tasks involving nginx module development, ngx_http_module_t, handler/filter/upstream implementation, pool allocation, or nginx configuration directives.
Curate Claude Code's auto-memory into durable project knowledge. Analyze MEMORY.md for patterns, promote proven learnings to CLAUDE.md and .claude/rules/, extract recurring solutions into reusable skills. Use when: (1) reviewing what Claude has learned about your project, (2) graduating a pattern from notes to enforced rules, (3) turning a debugging solution into a skill, (4) checking memory health and capacity.
Step-by-step guide to building AI agents from simple chat loops to autonomous multi-agent systems with tools, memory, and event-driven architecture
Expert Swift decisions Claude doesn't instinctively make: struct vs class trade-offs, @MainActor placement, async/await vs Combine selection, memory management pitfalls, and iOS-specific anti-patterns. Use when writing Swift code for iOS/tvOS apps, reviewing Swift architecture decisions, or debugging memory/concurrency issues. Trigger keywords: Swift, iOS, tvOS, actor, async, Sendable, retain cycle, memory leak, struct, class, protocol, generic
Expert-level C++ development with modern C++20/23, STL, memory management, and performance
Context compression and summarization methodology. Techniques for reducing token usage while preserving decision-critical information.
Apply systematic performance optimization techniques when writing or reviewing code. Use when optimizing hot paths, reducing latency, improving throughput, fixing performance regressions, or when the user mentions performance, optimization, speed, latency, throughput, profiling, or benchmarking.
Persistent shared memory for AI agents backed by PostgreSQL (fts + pg_trgm, optional pgvector). Includes compaction logging and maintenance scripts.