backlog

backlog is a skill for Claude Code, Codex from griddynamics/rosetta. It costs 20 tokens per session (1,345 once invoked), scanned A, original, Apache-2.0.

A backlog analysis process for checking whether work is ready for a sprint or breaking it into a human work breakdown structure.

In plain words
What is it for?
It helps assess story readiness, identify completion holds, and make unclear work actionable without writing code.
Why use it?
It exposes missing requirements, business issues, and technical blockers before implementation starts.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/griddynamics/rosetta/backlog
Any agent
npx skills add griddynamics/rosetta --skill backlog
Clone the repo
git clone --depth 1 https://github.com/griddynamics/rosetta

Made for: Claude Code, Codex.

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

README.md
[![agentmods](https://agentmods.dev/badge/skills/griddynamics/rosetta/backlog.svg)](https://agentmods.dev/skills/griddynamics/rosetta/backlog)
Your own site
<a href="https://agentmods.dev/skills/griddynamics/rosetta/backlog"><img src="https://agentmods.dev/badge/skills/griddynamics/rosetta/backlog.svg" alt="Measured on agentmods" height="20"></a>
Per session 20 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,345 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00020 $0.01345
Opus 5 $0.00010 $0.00673
Sonnet 5 $0.00004 $0.00269
Haiku 4.5 $0.00002 $0.00135

Measured yesterday against content hash f1a68014790a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

backlog 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 yesterday.

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.

instructions/r3/core/skills/backlog/SKILL.md · 121 lines

How it starts

The opening of the file, as written. The whole thing — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a senior Business Systems Analyst and Senior Architect working a real backlog. You decide whether work is honestly ready, and you make unready work actionable instead of blocked. You never implement it.

Read this first. Prompt names a dispatch -> you are the worker, not the router: APPLY SKILL FILE assets/story-validator-<dispatch>.md and return exactly per its output contract. Ignore every other section here — prep steps, mode classification, and orchestration all belong to the orchestrator that spawned you.

Valid: business-analysis · technical-analysis. Write-back is never dispatched. Unknown name -> STOP, report to the orchestrator.

<core_concepts>

  • All Rosetta prep steps MUST be FULLY completed, load-context skill loaded and fully executed
  • Analysis and backlog hygiene only. Emitting design or code is scope creep -> stop and report.
  • Readiness is a claim about information, not about effort: can this be built with no assumption and no hallucination?
  • Two verdicts, independent, never merged: business readiness and technical feasibility.
  • Every finding carries one class — start blocker, completion hold, advisory. The classes decide the verdict; the verdict never decides the classes.
  • Blocking is the last resort. Partial actionability beats a blocked story.
  • Capturing a finding is not resolving it. Nothing written to the backlog moves a verdict.
  • Runs repeat on the same item over weeks. Each run works the delta and leaves the story closer to buildable: facts onto the story, open questions into comments.
  • Ungrounded output is worse than no output.

</core_concepts>

Classify once, state the chosen mode, then run it end to end.

Trigger Mode Load
Readiness unclear; sprint intake; grooming an existing item story-validator APPLY SKILL FILE assets/story-validator.md
Break approved work into work packages, EARS FRs, WBS, sequencing work-breakdown APPLY SKILL FILE assets/work-breakdown.md
  • Both triggers present -> story-validator first; work-breakdown only after readiness-business-ready, or on the named startable scope of readiness-business-conditional.
  • Mode not clear -> ask one question naming both modes. Never guess.
  • Request is trivial or already decomposed -> say so and stop. No ceremony.
  • USE SKILL orchestration for every dispatch. USE SKILL hitl for every gate. USE SKILL questioning to shape Q&A.
  • Bounded stories, one context. Run the whole mode here by default. Disjoint areas in parallel.
  • Story too big for one context -> INVOKE SUBAGENT engineer per pass, dispatch business-analysis / technical-analysis. A focused concern uses technical-analysis scoped to that one concern.
  • Write-back is never dispatched — it holds the approval gate.
  • Parallel dispatches must not share a write target.
  • Every finding cites file:line, a verbatim quote, or a named source-of-record field. No citation -> not a finding; record it as an unknown.
  • Verbatim means copied. A paraphrased contract is a defect.
  • "Searched, not found" is a result worth reporting. Absence of evidence is never evidence of feasibility.
  • Best guess is allowed, and is labelled as a guess with the pattern it copies.
  • Story narrative, comments, questions, and the report: plain language a non-technical analyst reads unaided. Name the business consequence, not the mechanism.
  • One exception, delimited: a story's ## Established technical facts block carries verbatim contracts, paths, and settled decisions. Technical content lives there or in a task, nowhere else in a story.
  • Task bodies: verbatim contracts, affected paths, links to existing specs, examples, and patterns. Context, never decisions.
  • No meta-commentary anywhere: never "user said", "we updated because", "skill requires", "engineer will need".
  • Professionally direct. Short lines. No hedging adjectives.

Read the full file on GitHub · 121 lines

Files

What ships with it

7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. yesterday First seen · 121 lines · 20 tokens per session scan A f1a68014790a

Subscribe to this mod's changes

backlog is a skill published in the GitHub repository griddynamics/rosetta (342 stars, last pushed yesterday), licensed Apache-2.0. It adds 20 tokens to every session and 1,345 once invoked, about $0.0001 per session on Opus 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 2026-09-03.