Packs

7 packs

Memory, search and workflow skills from thedotmack/claude-mem.

19 skills · pack

Persistent memory system for Claude Code - seamlessly preserve context across sessions

5 skills · pack

C/C++ Debugging

For C/C++ developers needing debugging tools, memory analysis, and GDB integration.

8 skills · pack

Build RAG Pipeline with Pinecone

Build a production RAG pipeline and persistent agent memory using Pinecone as the vector database backend.

6 skills · pack

Token-compression suite: compressed chat mode plus commit, review, help, stats, memory-compress and subagent-crew skills by Julius Brussee.

7 skills · pack

Conversational derivation engine — generate agent-native memory architecture from natural conversation. 15 kernel primitives, 26 commands, 17 feature blocks, 3 presets.

10 skills · pack

@pwdev-solucoes

Spec-driven development framework v2.3 — 8 real subagents (incl. advisor), per-task model routing, curated memory graph, opt-in parallel waves, external CLI delegation (Codex/OpenCode/Kimi/Gemini/Kiro), simplification pass, strict verify, audit hooks, 22 commands

2 skills · pack

Results for “memory”

181 skills

Turn any rough prompt, half-formed idea, or task description into a finished, ready-to-send prompt optimized for Opus 4.8 (with adaptive thinking) inside the chat app — claude.ai, the Mac app, the iOS app — NOT the API. Use this skill whenever the user wants to write, rewrite, optimize, improve, sharpen, or polish a prompt for the chat app. Trigger phrases include "rewrite this prompt", "make this a better prompt", "optimize this prompt", "turn this into a prompt", "help me prompt this", "draft a prompt that...", "I want to ask...", or whenever the user pastes a draft prompt and asks for improvements. Also trigger when the user describes a task they plan to send into the chat app and clearly wants a reusable, well-structured prompt rather than a direct answer. The output is always a single, copy-pasteable prompt in a code block that the user sends as-is — never a template with placeholders. When the request concerns the user's own work, the skill retrieves the real specifics first — memory, meeting transcript