Packs

1 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

Results for “persistent-agent”

25 skills

azure-ai-agents-persistent-java

Create and manage persistent AI agents with threads, messages, runs, and tools using the Azure SDK for Java.

azure-ai-agents-persistent-dotnet

Create and manage persistent AI agents with threads, messages, runs, and tools using the Azure AI Agents SDK for .NET.

Orchestrates multi-agent project builds with persistent state, parallel execution, and atomic git commits.

Provides a persistent memory CLI for LLM agents, installed via npx.

Launches coordinated agent teams for tasks requiring persistent cross-talk, shared state, and lifecycle management, with team design, advisor coordination, and quality gates.

Build persistent multi-agent operating systems on Claude Code with kernel architecture, specialist agents, slash commands, file-based memory, and scheduled automation.

More results

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

sakamoto-family-smile

Builds a persistent multi-agent operating system on Claude Code using a kernel config, specialist agents, slash commands, file-based memory, and scheduled automation without external databases.

Adds a persistent pattern or rule that Ralph will remember and apply to future stories.

Drafts structured goal-loop prompts for long-running agent work with verifiable stop conditions, validation commands, and documentation requirements.

Provides persistent, compounding memory for AI agents across sessions using local markdown files, with optional Supabase-backed semantic search.

Provides a persistent, queryable virtual filesystem backed by SurrealDB for AI agents, with a Rust core and a Python agent interface.

Designs persistent memory architectures for AI agents, covering cross-session knowledge retention, entity tracking, temporal validity, graph/vector retrieval, and memory consolidation.

16.9k · bundle

harness-engineering

Prevent repeated AI coding-agent mistakes by turning failures into durable instructions, drift checks, regression tests, failure memory, and adoption reports tailored to the target repository.

continual-learning

Implements a continual learning loop for AI coding agents using hooks, two-tier memory (global and local), and automatic pattern detection to persist and apply learnings across sessions.

iterative-retrieval

Progressively refines context retrieval in multi-agent workflows to solve the subagent context problem.

Create and manage a Twitter/X agent with a persistent personality, automated posting workflows, and safety guardrails.

Builds persistent multi-agent workflows on Claude Code using a kernel config, specialist agents, slash commands, file-based memory, and scheduled automation without external databases.

continuous-agent-loop

Provides patterns for continuous autonomous agent loops with quality gates, evals, and recovery controls.

azure-ai-projects-dotnet

Manage Azure AI Foundry projects with .NET SDK: create and run agents, manage connections, datasets, deployments, evaluations, and indexes.

johnalbertini14-glitch

Persistent memory CLI for LLM agents. Store facts, recall past knowledge, link related memories, manage lifecycle.

agent-framework-azure-ai-py

Build persistent agents on Azure AI Foundry using the Microsoft Agent Framework Python SDK, with support for function tools, hosted tools, MCP servers, conversation threads, and streaming responses.

Mines SpecStory coding histories from any agent into a persistent corpus, surfaces reproducible workflows with corroborated evidence, and interactively forges chosen ones into skills installed across agent harnesses.

acontext-installer

Install and configure Acontext, a memory layer for AI agents that provides persistent sessions, file storage, and skill management.

Sets up persistent memory for AI agents on an OpenClaw gateway by installing a plugin that records observations and injects context into system prompts.