kano-agent-backlog-skill

Name: kano-agent-backlog-skill
Availability: InStock
Author: kanohorizonia

Plan and track AI-agent backlog items in a markdown-based store.

4|Updated Feb 16, 2026

Search Tags:#markdown #dashboards #adr #backlog #ai-agent #worklog

Ready to run

npx skills add https://github.com/kanohorizonia/kano-agent-backlog-skill --skill kano-agent-backlog-skill-kanohorizonia

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: kano-agent-backlog-skill
Source: https://github.com/kanohorizonia/kano-agent-backlog-skill/tree/main
Command: npx skills add https://github.com/kanohorizonia/kano-agent-backlog-skill --skill kano-agent-backlog-skill-kanohorizonia

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Local-first backlog skill provides a durable, markdown-based workspace to capture decisions, context, and rationale during agent-human collaboration, ensuring context survives across sessions and sessions.

Core Features & Use Cases

Structured backlog hierarchy (Epic → Feature → User Story → Task/Bug) with frontmatter metadata
Append-only Worklogs and Architecture Decision Records (ADRs) for auditable decisions
Ready gate enforcement and multi-agent coordination to keep work aligned
Local, version-controlled dashboards and views generated from Markdown artifacts

Quick Start

Initialize a local backlog for your project using the Kano backlog CLI and begin by creating your first backlog item.

Frequently Asked Questions about kano-agent-backlog-skill

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

FAQPage Schema

How do I track an AI agent backlog locally without a server?▼

You can track an AI agent backlog locally without a server by using this markdown-based skill to capture items hierarchically. It bootstraps via CLI, stores data as local markdown files, and generates version-controlled dashboards.

What is the best way to manage multi-agent coordination and worklogs?▼

The best way to manage multi-agent coordination is using a durable markdown backlog with append-only worklogs. This approach ensures context survives across sessions and keeps multiple agents aligned without requiring external databases.

How does a Ready gate enforce quality in a backlog hierarchy?▼

A Ready gate enforces backlog quality by validating structured items like Epics, Features, and User Stories before execution. It checks frontmatter metadata to ensure tasks and bugs meet defined criteria for agent processing.

Can I use markdown dashboards to track Architecture Decision Records for AI agents?▼

Yes, you can use markdown dashboards to track Architecture Decision Records. The skill creates append-only ADRs to capture auditable decisions and refreshes local views from these markdown artifacts automatically.

Do I need a database to maintain AI agent context across sessions?▼

No, you do not need a database to maintain AI agent context across sessions. This skill provides a local-first workspace that saves decisions, rationale, and worklogs directly as markdown files in your repository.

What backlog item types are supported for local AI agent planning?▼

Backlog item types supported for local AI agent planning include Epic, Feature, User Story, Task, and Bug. These hierarchical items are managed with frontmatter metadata to structure planning and tracking effectively.