memory-slices

Manage and retrieve memory slices for workflow nodes.

103|1|Updated Jun 9, 2026

Search Tags:#memory management #workflow optimization #agentic workflows #issue resolution #recurrence tracking

Ready to run

npx skills add https://github.com/blueif16/PiFlow --skill memory-slices

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: memory-slices
Source: https://github.com/blueif16/PiFlow/tree/main/.claude/skills/memory-slices
Command: npx skills add https://github.com/blueif16/PiFlow --skill memory-slices

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill manages and retrieves memory slices for each node in a workflow, ensuring that historical lessons and recurring issues are recorded and used to improve future runs.

Core Features & Use Cases

Memory Slicing: Captures and maintains a node's history of failures and successes, including root causes and preventive measures.
Recurrence Tracking: Tracks how often a specific issue has occurred across different runs.
Freshness Validation: Ensures that the lessons are up-to-date with the latest code changes.
Use Case: When a node in a workflow fails, this Skill can quickly identify if it's a recurring issue or a one-off problem, allowing for more informed decision-making.

Quick Start

Use the memory-slices skill to retrieve the memory slice for a specific node in your workflow.

Frequently Asked Questions about memory-slices

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I track recurring workflow failures in agentic workflows?▼

Workflow memory slices capture a node's failure history and root causes within memory.md files. They record historical lessons and preventive measures to ensure past issues inform and improve future agentic workflow runs.

How do I validate lesson freshness for optimized workflow performance?▼

To validate lesson freshness, this Skill checks recorded memory slices against the latest code changes. It ensures that the lessons applied for workflow optimization remain accurate and up-to-date with the current codebase.

Do I need memory.md files to use memory slicing for issue resolution?▼

Yes, memory.md files are required. This Skill reads and writes node memory slices to these files to capture failure history and track recurring issues during workflow execution.

What is the best way to maintain node history in agentic workflows?▼

The best way to maintain node history is by capturing memory slices that track failures, successes, and root causes. This approach validates lesson freshness and records recurrence counts to optimize workflow performance.

Why does a workflow node keep failing across different runs?▼

A node fails repeatedly due to unresolved root causes. This Skill tracks issue recurrence across runs by referencing memory slices, allowing you to identify whether the failure is a recurring issue or a one-off problem.