pbl-skills

Product Backlog management for pi and Claude Code — skills, extensions, and tools to manage a product backlog inside your repo

Packages

Package details

extensionskill

Install pbl-skills from npm and Pi will load the resources declared by the package manifest.

$ pi install npm:pbl-skills
Package
pbl-skills
Version
1.3.0
Published
Jun 1, 2026
Downloads
300/mo · 17/wk
Author
melomario
License
MIT
Types
extension, skill
Size
103.2 KB
Dependencies
0 dependencies · 2 peers
Pi manifest JSON
{
  "extensions": [
    "./index.ts"
  ],
  "skills": [
    "./skills"
  ],
  "image": "https://f004.backblazeb2.com/file/npm-stuff/pi-pbl-skills/screenshot.png",
  "video": "https://f004.backblazeb2.com/file/npm-stuff/pi-pbl-skills/pbi-skills.mp4"
}

Security note

Pi packages can execute code and influence agent behavior. Review the source before installing third-party packages.

README

pbl-skills

Product Backlog management for pi — commands, tools, and skills to manage your product backlog inside your repo.

pbl-skills turns your repo into a lightweight product management workspace. It structures your backlog as plain markdown folders, gives you interactive TUI widgets for visualization and reordering, and bundles a suite of AI-assisted skills for creating, refining, splitting, and completing backlog items.

Read The Product Backlog Should Live in Your Repo for the theory behind this approach.


Why?

Problem How pbl-skills solves it
Backlog lives in Jira/Notion, far from the code Backlog lives in product-backlog/ — same repo, same branch
Prioritization gets stale Interactive reorder via /pbl-view --order (or press o in the view) makes it effortless
Stories aren't ready to code Structured 3 C's pipeline: Card → Conversation → Confirmation
No visibility into backlog health Anti-pattern scanner detects bottlenecks, stale items, over-refinement
Too much manual bash Tools like create_backlog_item replace mkdir + write calls

Installation

pi install -l npm:pbl-skills

What you get

4 Commands (TUI widgets)

Command What it does
/pbl-view Segmented progress bar + color-coded item list. Supports --order for interactive reorder, --widget for static widget.
/pbl-metrics Backlog health check + velocity sparkline — scans for 5 anti-patterns and shows a health widget + status bar indicator
/pbl-done Interactive "mark as done" selector (with keyboard search/filter)
/pbl-timeline Chronological event history (created, refined, confirmed, done, split)

3 Tools (LLM-callable)

Tool What it does
create_backlog_item Creates a new PBI folder with Card.md and history entry — no bash needed
split_backlog_item Splits an item using Hamburger Method results — updates original + creates new
show_backlog_widget Toggles the visualization widget programmatically

7 Skills (AI-assisted workflows)

Skill What it does
pbl-kickoff Bootstrap a full product idea into backlog items (structured interview)
pbl-add Add a new item with a short 3-question interview (creates CONNEXTRA Card)
pbl-refine Refine a raw item through a structured 3 C's interview
pbl-split Split a large item into two independent items (Hamburger Method)
pbl-implement Bridge from a refined item to coding — generates test skeleton + identifies design files
pbl-diagnose Deep analysis of backlog health — identifies anti-patterns, explains root causes, and offers to act on flagged items
pbl-done Mark an item as done with Definition of Done gate

Scripts

Script What it does
scripts/pbl-index.js Regenerates product-backlog/.index.md (item counts, status summaries, recent history)

How it works

The 3 C's pipeline

Every backlog item progresses through three states, tracked by which files exist:

raw        refined       ready
  ● ──────→ ◉ ────────→ ◆
Card.md    +Conversation.md   +Confirmation.md
  • raw — just a Card.md with a CONNEXTRA story (As a… I want… So that…)
  • refinedCard.md + Conversation.md (structured refinement decisions)
  • ready — all three files present, ready for /pbl-implement to bridge into code

Folder structure

product-backlog/
├── CLAUDE.md              ← auto-generated guide for AI agents
├── .index.md              ← auto-generated index (fast path for diagnosis)
├── .history/              ← one file per event: YYYY-MM-DD_{slug}_{event}
├── .removed-items/        ← soft-deleted items (can be restored)
├── done/                  ← completed items
├── 0010-user-login/
│   ├── Card.md            ← CONNEXTRA user story
│   ├── Conversation.md    ← refinement decisions
│   └── Confirmation.md    ← prose acceptance criteria
├── 0020-profile-page/
│   └── Card.md
└── 0030-payment-flow/
    ├── Card.md
    └── Conversation.md

Anti-pattern detection

/pbl-metrics checks for 5 common issues:

  1. Refinement bottleneck — >3 items discussed but never confirmed
  2. Ready but not started — >5 items fully refined, waiting
  3. Stale refined — item refined 5+ done events ago (may be outdated)
  4. Stale unrefined — item created 8+ events ago, never refined
  5. DoD may be staledocs/adr/ has files newer than the Definition of Done

Additionally, /pbl-metrics shows a delivery velocity sparkline (last 10 weeks).

The status bar shows a live indicator: 🟢 healthy, 🟡 warnings, 🔴 errors.


Quickstart

# 1. Install the package
pi install -l npm:pbl-skills

# 2. Start pi (or Claude Code) in your repo
pi

# 3. Kickoff a new product (or add items one by one)
/pbl-kickoff

# 4. View your backlog
/pbl-view

# 5. Refine the top unrefined item
/pbl-refine

# 6. Check health + velocity
/pbl-metrics

# 7. Start coding
/pbl-implement

Requirements

  • pi (@earendil-works/pi-coding-agent) — peer dependency
  • typebox — for tool parameter validation (peer dependency)
  • Node.js ≥ 18

License

MIT