backlog-prioritization

backlog-prioritization is a skill for Claude Code from iBrain-BVBA/gutt-claude-code-plugin. It costs 133 tokens per session (2,590 once invoked), scanned A, original, MIT.

A workflow for ordering part of a Jira backlog using evidence from tickets, decisions, customer commitments, dependencies, and incidents. A backlog is the list of planned or requested work that has not been completed.

In plain words
What is it for?
Ranking Jira work, citing the evidence for each position, identifying related requests or prerequisites, and preparing a short leadership summary.
Why use it?
It makes the reasons behind a proposed order visible instead of relying only on ticket fields. The result remains a recommendation for people responsible for deciding priorities.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the gutt-product plugin — 3 skills shipped together

Good fit Ranking Jira work, citing the evidence for each position, identifying related requests or prerequisites, and preparing a short leadership summary.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ibrain-bvba/gutt-claude-code-plugin/backlog-prioritization
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add iBrain-BVBA/gutt-claude-code-plugin --skill backlog-prioritization
Clone the repo
git clone --depth 1 https://github.com/iBrain-BVBA/gutt-claude-code-plugin

Made for: Claude Code.

Or install gutt-product, the plugin that ships this one along with the rest of its 3 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for backlog-prioritization

README.md
[![agentmods](https://agentmods.dev/badge/skills/ibrain-bvba/gutt-claude-code-plugin/backlog-prioritization/github.svg)](https://agentmods.dev/skills/ibrain-bvba/gutt-claude-code-plugin/backlog-prioritization)
Your own site
<a href="https://agentmods.dev/skills/ibrain-bvba/gutt-claude-code-plugin/backlog-prioritization"><img src="https://agentmods.dev/badge/skills/ibrain-bvba/gutt-claude-code-plugin/backlog-prioritization/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for backlog-prioritization

Your own site · 80×15
<a href="https://agentmods.dev/skills/ibrain-bvba/gutt-claude-code-plugin/backlog-prioritization"><img src="https://agentmods.dev/badge/skills/ibrain-bvba/gutt-claude-code-plugin/backlog-prioritization.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 133 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,590 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00133 $0.02590
Opus 5.5 $0.00053 $0.01036
Sonnet 5.5 $0.00027 $0.00518
Haiku 4.5 $0.00013 $0.00259

Measured 1mo ago against content hash 69a726eb88a6, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

backlog-prioritization scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

gutt-product/skills/backlog-prioritization/SKILL.md · 207 lines

How it starts

The opening of the file, as written. The whole thing — 207 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Backlog Prioritization

A backlog ordered on ticket fields alone re-decides things the organization has already decided. The evidence that changes the order is usually not in the tickets: a commitment made to a client, a decision that makes one item a prerequisite for three others, an area that has produced two incidents this quarter, a cluster of requests that are really one feature. This skill puts that evidence next to each item and reports the order it implies — plus a summary short enough to open a leadership conversation rather than postpone it.

The order is a proposal. Ranking is an act of authority that stays with the people accountable for the outcome; this skill's job is to make their decision better informed, and to be explicit about where its own evidence runs thin.

Underneath, memory-search owns the search ladder and the relevance gate, graph-traversal owns relationship walking, and memory-capture owns any durable write; they ship with the gutt-pro plugin (this plugin depends on it). Without them, follow the rules below and note the gap in one line. Jira access comes from whatever Atlassian tooling the session surfaces; names and prefixes vary per install.

Hard rules (non-negotiable — read first)

  1. Jira is read-only here — never write an order into it. No rank field, no priority field, no sprint or fix-version assignment, no status changes, no edits to any other field. The output is a proposal in the reply. The one permitted write is a comment, drafted and posted only after the user approves the exact text in this session. Treat it as final — approval is the gate, not an undo; a truly needed correction re-approves the text and targets the existing comment if the tool allows, rather than posting a second one. Write markdown and set the tool's content-format parameter to markdown when it exposes one.
  2. Every item's position carries its reason, and thin evidence says so. Each ranked item gets the evidence that placed it there. An item whose only input is its own ticket fields is labelled no memory evidence and stays where the board already had it — moving an item on no evidence is the one failure mode this skill must never have. Never let a confident tone stand in for a citation.
  3. The criteria come from the organization, not from this skill. Read what the project actually ranks on before ranking anything: the issue type's own field schema, and the values present on the slice. Where custom fields carry value, effort, risk, client, or commitment data, rank on those and name them in the output. Never import an outside scoring framework, never invent weights the organization has not agreed, and never hardcode a field name — discover them per project, and where nothing rankable is exposed, say so and fall back to the visible order plus rule 4's evidence.
  4. Evidence is the differentiator, and it is specific. Four kinds move an item: a decision or commitment that binds it, a dependency that makes it block or wait on other items, history in the area it touches (incidents, repeated rework), and overlap with other items in the slice. Where a backlog-dedupe run's clusters are in the session, they are the overlap evidence, cited as such and carrying each cluster's own evidence label — a similarity only cluster stays similarity only here; otherwise step 3's own search covers it. Each one enters the output with its source and date, or it does not enter.
  5. Every claim is real and cited — a Jira key, or a memory episode, lesson, decision, or incident with its id and date. No invented history, no commitment attributed to a client that no record shows, no dependency the graph does not carry.
  6. Org scope is checked at the output — pass explicit group_ids naming the org group on reads (take the name from session results or ask; never guess one), treat scope as server-decided, and before any item of evidence enters the summary or an offered comment, confirm that item's own scope is the org group. Personal-scope material stays in the in-session output. A summary written for a client audience carries nothing from another client's engagement — check this per line, not per run. Bare tool names, probed with ToolSearch. No memory writes — a durable prioritization rationale goes through memory-capture's gate.

Read the full file on GitHub · 207 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago Changed · +5 lines 69a726eb88a6
  2. 1mo ago First seen · 202 lines · 133 tokens per session scan A ec6a7c334101

Subscribe to this mod's changes

backlog-prioritization is a skill published in the GitHub repository iBrain-BVBA/gutt-claude-code-plugin (5 stars, last pushed 1mo ago), licensed MIT. It adds 133 tokens to every session and 2,590 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other skills, from other repositories

story-readiness

Checks whether a story is ready to implement: clear acceptance criteria, no open questions, valid ADR and dependencies. Use when the user asks if a story, or the sprint's stories, are ready to start or build.

Donchitos/Claude-Code-Game-Studios · 48 tokens

recipe-create-meet-space

Create a Google Meet meeting space and share the join link.

googleworkspace/cli · 18 tokens

workthreads

SpecStory Workthreads - a weekly work-thread rollup across a team's repos from SpecStory coding histories (any agent - Claude Code, Codex, Cursor, Gemini, and more). It groups the window's sessions into threads of work per project and labels each new / open / recently closed, so a lead sees what shipped, what is still…

specstoryai/getspecstory · 126 tokens

atmos-config

Atmos root configuration: atmos.yaml discovery, precedence, deep merging, basepath, imports, minimal bootstrap, and routing to narrower Atmos skills.

cloudposse/atmos · 31 tokens

projects

List all managed projects with status, branch, open PRs, and open issue counts — portfolio-level view.

me2resh/apexyard · 24 tokens

handle-linkedin-connection-request-signal

Use this skill when someone sends a team member an inbound LinkedIn connection request. An inbound request is a deliberate, ACTIVE first-party intent signal — meaningfully stronger than a passive profile view — and it deserves different scoring rules. The skill resolves and enriches the requester, gates them through…

swan-gtm/gtm-skills · 160 tokens