Running Log

Captures and organizes ideas, consultations, and process memories into a structured, tagged backlog with cross-entry linking.

Updated Dec 21, 2025
One-click install
npx skills add https://github.com/jcmrs/jcmrs-plugins --skill running-log
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: Running Log
Source: https://github.com/jcmrs/jcmrs-plugins/tree/main/plugins/running-log/skills/running-log
Command: npx skills add https://github.com/jcmrs/jcmrs-plugins --skill running-log

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Persistent schema-driven running log that captures ideas, consultations, and process memory across sessions, enabling structured backlogs and cross-session learning.

Core Features & Use Cases

  • Three-component architecture: human quick-capture, AI auto-detection, and librarian backlog review.
  • Self-organizing backlog with timestamps, tags, and cross-entry linking for context.
  • Useful for knowledge work, product development, and engineering teams to retain reasoning and decisions.

Quick Start

Capture a quick idea with /idea followed by a one-line description to begin building your persistent backlog.

Frequently Asked Questions about Running Log

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

FAQPage Schema
How do I persist ideas and reasoning across chat sessions?

To persist ideas across sessions, you need a structured running log that captures consultations and process memory, enabling cross-session learning. This skill organizes entries with timestamps, tags, and cross-entry linking to retain reasoning over time.

How do I capture a quick idea during an AI interaction?

You can capture a quick idea by typing /idea followed by a one-line description. This triggers the human quick-capture workflow, immediately saving your thought as a structured entry into the persistent backlog for later review.

Can AI auto-detect and log decisions without manual input?

Yes, AI auto-detection works during interactions to identify and log decisions automatically. It captures process memories into the structured backlog using deterministic entry fields and auto-tagging without requiring manual commands from the user.

What is the best way to review a cross-session decision backlog?

The best way to review a cross-session decision backlog is using a librarian-backed review process. By running /review-backlog, you surface insights through post-processing links that connect related entries across your structured log history.

Does this cross-session memory log work for engineering teams?

Yes, this cross-session memory log works for engineering teams and product development. It helps knowledge workers retain reasoning and decisions in a self-organizing backlog, ensuring structured context is preserved across collaborative project sessions.