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Agent skill

Backlog Refinement

by borghei in borghei/Claude-Skills

Backlog refinement playbook covering INVEST quality, vertical story splitting, Definition of Ready, and Definition of Done -- with a Python scorer that grades each story against INVEST and emits a…

MITAuto-check passedProduct & Project Management

Install Backlog Refinement

skills CLI
$ npx skills add borghei/Claude-Skills --skill backlog-refinement -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install borghei/Claude-Skills backlog-refinement --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/project-management/execution/backlog-refinement .claude/skills/backlog-refinement && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
backlog-refinement
GitHub stars
874
Token cost
~1.7k tokens
SKILL.md length
740 words
Files
7 (incl. scripts, references, assets)
Skills in repo
364
Repo updated
First seen
Licence
MIT

At a glance

Backlog refinement playbook covering INVEST quality, vertical story splitting, Definition of Ready, and Definition of Done -- with a Python scorer that grades each story against INVEST and emits a…

  • Tasks that involve Sprint planning and agile
  • SKILL.md covers Overview, Core Capabilities, When to Use and Clarify First, plus 4 more sections
  • Runs Python scripts from its folder; calls python
  • Tasks that involve User stories

What it does

Backlog Refinement is an agent skill from borghei/Claude-Skills. Backlog refinement playbook covering INVEST quality, vertical story splitting, Definition of Ready, and Definition of Done -- with a Python scorer that grades each story against INVEST and emits a ready/not-ready verdict.

Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts, reference files and assets (for example `assets/refinement_checklist.md`, `examples/refining-12-stories.md` and `references/invest-and-splitting-guide.md`).

It sits in Product & Project Management, covering Sprint planning and agile and User stories. It works with Python. The repository describes itself as: 385 AI skills, 77 expert agents, and 900 stdlib Python tools for every team: engineering, PM, marketing, C-level, compliance, business ops, research, and a LinkedIn toolkit… The licence is MIT.

When your agent uses it

  • Tasks that involve Sprint planning and agile
  • Tasks that involve User stories

Example prompts

  • “/backlog-refinement”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit c9a1487. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Backlog Refinement loads about 1.7k tokens when it runs, and up to ~12k if it reads all its reference files. Until then it costs about 60 tokens; SKILL.md has 740 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~60
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~12k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from borghei/Claude-Skills at commit c9a1487, republished under its MIT licence (© borghei). 740 words, ~1,666 tokens.

Download SKILL.mdSave it as .claude/skills/backlog-refinement/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.
name
backlog-refinement
description
Backlog refinement playbook covering INVEST quality, vertical story splitting, Definition of Ready, and Definition of Done -- with a Python scorer that grades each story against INVEST and emits a ready/not-ready verdict.
license
MIT + Commons Clause
metadata.version
1.0.1
metadata.author
borghei
metadata.category
project-management
metadata.domain
pm-execution
metadata.updated
2026-06-15
metadata.python-tools
refinement_scorer.py
metadata.tech-stack
invest, story-splitting, definition-of-ready, definition-of-done

Backlog Refinement Expert

Overview

Refinement is the most under-invested ritual in agile teams. Stories arrive at sprint planning oversized, ambiguous, or strategically disconnected, and the team spends planning meetings doing what should have happened the week before. This skill is the refinement playbook: grade stories against INVEST, split them vertically (so each slice ships value end-to-end), and keep a working Definition of Ready and Definition of Done that prevent half-baked work from entering or leaving a sprint.

The skill includes a Python scorer (refinement_scorer.py) that grades each story in a JSON backlog against the six INVEST criteria and outputs a readiness score (0-6) per story. Stories scoring 5-6 are sprint-ready; 3-4 need targeted refinement; below 3 go back to discovery.

This complements wwas/ (Why-What-Acceptance format) and job-stories/ (JTBD format). Either format produces stories; this skill grades them and gets them sprint-ready.

Core Capabilities

  • INVEST grading — score each story across Independent, Negotiable, Valuable, Estimable, Small, Testable (0-6) and triage by score.
  • Vertical story splitting — the 9 Lawrence recipes + SPIDR taxonomy; avoid horizontal (layer/team/sprint) splits.
  • Definition of Ready / Done — input and output quality gates with enforceable templates.
  • Refinement session structure — cadence, candidate volume, triage routing into discovery or planning.

When to Use

  • Weekly refinement session -- grade next-sprint candidates against INVEST and split anything too large.
  • Backlog hygiene sweep -- re-grade the top 30 items and retire what no longer connects to strategy.
  • Sprint planning input -- confirm all candidates pass DoR before planning.
  • New team onboarding -- establish a shared definition of "ready" and "done."
  • Velocity diagnosis -- erratic sprint completion usually traces to refinement quality.

When NOT to use: pure technical task lists with no user-facing outcome (use a simpler checklist); ad-hoc bug triage (different lifecycle); unscoped work (send to discovery/ first).

Clarify First

Before grading the backlog, confirm these inputs. If any is unknown or vague, ASK — do not assume:

  • The stories — the actual backlog items in the user's words, with their acceptance criteria (drives every INVEST score and which slicing recipe applies)
  • Team's Definition of Ready — what "ready" means for THIS team (DoR must be team-authored to be enforced; sets the promote/refine/return gate)
  • Sprint size / "small enough" bar — sprint length and rough capacity (sets how far a story must be split before it counts as Small)

Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.

Quick Start

bash
python scripts/refinement_scorer.py --input backlog.json --format markdown   # grade a backlog
python scripts/refinement_scorer.py --demo --format markdown                 # inspect demo + output

Triage by score: 5-6 promote to Refined, 3-4 discuss and fix the failing criteria, 0-2 send back to discovery.

Show full SKILL.md (317 more words)Show less

References

Load the reference that matches the task — keep this file lean and pull detail on demand:

  • references/refinement-playbook.md — full INVEST table, the 9 splitting recipes + SPIDR, DoR/DoD templates and anti-patterns, the step-by-step workflow, the refinement_scorer.py reference (flags, input JSON, scoring rubric), troubleshooting, and success criteria. Read when running a refinement session or wiring the scorer.
  • references/invest-and-splitting-guide.md — deep dive on INVEST (Wake), the 9 Lawrence patterns, SPIDR (Cohn), and worked horizontal-vs-vertical split examples. Read when a story is hard to split or a slice feels wrong.
  • references/red-flags.md — concrete examples of how refinement output goes wrong, why it's bad, and how to fix it. Read when reviewing a refined backlog or diagnosing recurring quality issues.
  • assets/refinement_checklist.md — ready-to-use DoR and DoD checklists plus a refinement session agenda. Use during a live session.

Scope & Limitations

In Scope: INVEST grading of individual stories; vertical splitting (9 Lawrence patterns + SPIDR); DoR/DoD templates and enforcement; refinement session structure and cadence; the Python scorer.

Out of Scope: authoring stories from scratch (wwas/, job-stories/); prioritization/sequencing (prioritization-frameworks/); sprint planning/capacity/velocity (../scrum-master/); discovery and problem framing (discovery/); estimation techniques (agile-coach/).

Caveats: INVEST is a heuristic — a 6/6 story can still be the wrong story (pair with prioritization-frameworks/ and discovery/identify-assumptions/). DoR/DoD must be team-authored to be enforced. The scorer grades structural form, not strategic substance.

Integration Points

IntegrationDirectionDescription
execution/wwas/Receives fromWWAS-format stories enter refinement to be graded and split
execution/job-stories/Receives fromJob stories enter refinement to be graded and split
execution/prioritization-frameworks/Pairs withPrioritization sets the sequence; refinement makes the top N executable
discovery/identify-assumptions/Sends toStories scoring 0-2 are sent back for assumption mapping
discovery/brainstorm-experiments/Sends toStories with unvalidated assumptions become experiment candidates
../scrum-master/Feeds intoRefined stories feed sprint planning; refinement quality drives velocity stability
execution/status-update-generator/IndirectDoD compliance feeds the "what's done this week" section of status updates
../jira-expert/Pairs withRefined stories become Jira tickets with structured fields and DoR/DoD checklists

© borghei, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 6 other files (scripts, references, assets) in project-management/execution/backlog-refinement of borghei/Claude-Skills.

  • SKILL.md
  • assets/refinement_checklist.md
  • examples/refining-12-stories.md
  • references/invest-and-splitting-guide.md
  • references/red-flags.md
  • references/refinement-playbook.md
  • scripts/refinement_scorer.py

Open the folder on GitHubat commit c9a1487

Compare with similar skills

Backlog Refinement next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Backlog Refinement compared with similar skills
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Backlog Refinement this skillborghei/Claude-Skills874—~1.7kAutomated safety check: PassMIT
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Walking Skeleton Roadmap Scopingprime-radiant-inc/iterative-development181—~1.7kAutomated safety check: PassApache-2.0
Taigapenpot/penpot61k—~778Automated safety check: PassMPL-2.0
Epic Breakdown Advisordeanpeters/Product-Manager-Skills7.2k1 repos~6kAutomated safety check: PassCustom licence
Bmad Sprint Planningdelorenj/mcp-server-trello4465 repos~3kAutomated safety check: PassMIT

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Works with

Categories

Questions about Backlog Refinement

What does Backlog Refinement do?

Backlog refinement playbook covering INVEST quality, vertical story splitting, Definition of Ready, and Definition of Done -- with a Python scorer that grades each story against INVEST and emits a…. Backlog Refinement is an agent skill from borghei/Claude-Skills. Backlog refinement playbook covering INVEST quality, vertical story splitting, Definition of Ready, and Definition of Done -- with a Python scorer that grades each story against INVEST and emits a ready/not-ready verdict.

When should I use Backlog Refinement?

Backlog Refinement fits situations like: tasks that involve Sprint planning and agile; tasks that involve User stories.

How do I install Backlog Refinement in Claude Code?

Run `npx skills add borghei/Claude-Skills --skill backlog-refinement -a claude-code`. Or copy the skill folder (project-management/execution/backlog-refinement in borghei/Claude-Skills) into .claude/skills/backlog-refinement in your project. Claude Code loads it when a task matches its description.

How do I install Backlog Refinement in Codex?

Run `npx skills add borghei/Claude-Skills --skill backlog-refinement -a codex`. Or copy the skill folder (project-management/execution/backlog-refinement in borghei/Claude-Skills) into .agents/skills/backlog-refinement in your project. Codex loads it when a task matches its description.

Can I use Backlog Refinement in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add borghei/Claude-Skills --skill backlog-refinement -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/backlog-refinement, .gemini/skills/backlog-refinement, .github/skills/backlog-refinement and .opencode/skills/backlog-refinement in your project.

What does Backlog Refinement need to run?

Going by SKILL.md and its folder, Backlog Refinement needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Backlog Refinement access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Backlog Refinement safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Backlog Refinement use?

Backlog Refinement is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Backlog Refinement use?

About 1.7k tokens (SKILL.md is roughly 6.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 10k tokens, read only when the agent opens those files.

What are the alternatives to Backlog Refinement?

Skills that share tags, products or a category with Backlog Refinement: Agile Product Owner (alirezarezvani/claude-skills, 28k stars), Walking Skeleton Roadmap Scoping (prime-radiant-inc/iterative-development, 181 stars), Taiga (penpot/penpot, 61k stars) and Epic Breakdown Advisor (deanpeters/Product-Manager-Skills, 7.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Backlog Refinement?

borghei (a GitHub user) maintains it in borghei/Claude-Skills, which has 874 GitHub stars. The repository holds 364 skills in this directory. The repository was last updated on October 7, 2026.

Source: borghei/Claude-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.