Hire an AI sprint priority planner

Everything it can hand back

Your task sets the actual outputs. The specialist picks the methods that cover them.

• A ranked list with a value and effort rating for each item, and a RICE score where you gave the numbers
• A line showing what fits in your real capacity, and what is stretch
• The items that wait, each with a one-line reason
• The dependencies and risks that could break the plan
• A short note for each stakeholder who lost out

How it does the job well

• RICE needs reach, impact, confidence and effort. Compute a score only when the user gave all four, or when you show each as an ESTIMATE with the reason. If the data is missing, write "not enough data" and rank by value and effort ratings (high, medium, low) marked as rough.
• Never invent reach, revenue, effort days or velocity. Use the user's numbers, or label a guess ESTIMATE and say what would replace it.
• The profile's capacity defaults (meeting overhead near 15 to 20 percent, a buffer near 15 percent) are starting values. If the user gave their own figure, use it. If not, say which default you used.
• If one item is really two jobs, split it and say so.
• Do not change a tool, assign work to a person or message a stakeholder. Prepare drafts and ask first.
• Start from the user problem and the evidence for it, then the solution.
• Write decisions down with the reason and the options you rejected.

Mistakes it avoids

• Ranking by who asked, not by value for effort.
• Filling the sprint to 100 percent of capacity.
• Copying the profile's targets (such as "90 percent of points delivered") as the user's results.
• Giving a precise score from vague inputs.
• Treating opinions or one loud request as proven demand.
• Specs that skip edge cases, error states or dependencies.

What a good result looks like

An example, not your task: Your backlog has 40 items and the team can do 8, and people are arguing about which.

• Sprint goal. One line on what the sprint is for and how you will know it worked.
• Capacity. Working days after time off and meetings, the buffer held back, and the days left to commit.
• Ranked backlog. Every item ranked, with a value rating, an effort estimate, a RICE score where possible and a group.
• The line. What is committed, what is stretch and what waits, each waiting item with a reason.
• Dependencies and risks. Items that block others or need outside help, and what could break the plan.
• Trade-offs to explain. A short message for each person whose request waits.

How the work is checked

• Every requirement can be tested.
• Assumptions and risks are listed with how each will be checked.
• Dependencies and owners are named.
• States which checks passed, failed or could not run, and names missing inputs.

These checks have not been run against a model yet. Your AI uses them to check its own work.

A second opinion

Before it hands back, your AI reviews the draft the way Peter Drucker would. This is a way of reviewing the work. It does not mean they wrote or endorse it.

Capabilities

• Fix the goal and the capacity. It states the sprint goal in one line. It works out real working days after time off and meetings, and asks once for what is missing.
• Score each item. It rates value and effort for every item. It adds a RICE score only where you gave reach, impact, confidence and effort.
• Sort into groups. It labels each item a quick win, a big project, a fill-in or a time sink, and flags items that are really two jobs.
• Check dependencies. It finds items that block other items, or that need a person or a team outside yours, and moves them earlier or later.
• Draw the line. It adds items until capacity minus a buffer is full. What is above is committed, the next few are stretch, the rest wait.
• Prepare the trade-offs. It writes a short reason for each item that waits, and lists the risks that could break the plan.

How the role works

1. Checks your task, context and available tools.
2. Picks the methods needed and prepares a work plan.
3. Carries out supported tasks, with each method's limits and review gates.
4. Checks the real deliverables and corrects supported faults.
5. Hands back files, evidence and unresolved gaps.

Your specialist's working setup

Download the base specialist without a task form or account. README.md and SETUP.md explain how to use the folder. SOUL.md defines its scope. INTAKE.md asks missing questions inside your AI. PLAYBOOK.md, SKILLS.md, BEST_PRACTICES.md, CHECKS.md and HANDOFF.md guide the work and its checked deliverables.

Complete associated skills, supporting files and licences are included. Choose only the methods needed for the actual task. Keep context, working files and accepted feedback in your AI project.

Use this specialist through MCP or the API

Call prepare_specialist with role_id product-sprint-prioritizer only. No task is required to load it. Your AI asks what job you need done, what you want back and which relevant context it can use.

For task-led hiring, call find_specialist, explain the suggested specialists and let the user accept or change the team.

Complete ZIP: Download base specialist. API: GET /api/v1/specialists/product-sprint-prioritizer/pack. The host AI supplies its own model, tools and execution; a pack does not connect accounts or run a task.

Inputs and helpful context

The specialist starts from the task brief. Only active methods require their inputs.

For the primary method, when used

• Your backlog, one line per item, with a short note on what each is for
• Your team size, the days each person can work this sprint, and any time off or fixed meetings
• The goal for this sprint or what the business needs most right now
• Any numbers you have, such as how many users an item affects or what it is worth (optional)
• What the team finished in the last few sprints (optional)

Helpful context (optional)

• The days each item took last time, if you have them. They make estimates more honest.
• Which items a client or boss has already been promised.
• Any hard deadline, such as a launch date or a contract date.

Tools and access

• Claude, ChatGPT or Gemini with file upload: It can read a backlog exported from Jira, Linear, Trello or a spreadsheet, and check the sum of effort against capacity.

Functions and deliverables

• Sprint priority planner: Pick what your team builds next sprint. Paste your backlog and team capacity to get a ranked list, what fits, what waits and what to tell people.
  • A ranked list with a value and effort rating for each item, and a RICE score where you gave the numbers
  • A line showing what fits in your real capacity, and what is stretch
  • The items that wait, each with a one-line reason
  • The dependencies and risks that could break the plan
  • A short note for each stakeholder who lost out
  Source: Michael Sitarzewski and Agency Agents contributors.
• Sprint plan writer: Give it your backlog and team time off. Get sprint scope, goals and a stretch list sized to real capacity.
  • One sprint goal in a single sentence
  • A capacity table that takes off time off and meetings
  • Items sorted into must-do, should-do and stretch
  • A list of risks and what to do about each
  • Key dates and a Definition of Done checklist
  Source: Anthropic.
• Priority method picker: Pick the best way to prioritize your backlog (RICE, ICE or Opportunity Score) and get a scoring table for your own list, with the steps to use it.
  • One recommended method and a runner-up, with the reason for each
  • The formula and the meaning of each score
  • A scoring table with one row for each of your items
  • A guide to reading the ranking and checking it
  • A list of the numbers you still have to collect
  Source: Pawel Huryn.
• Team stop-doing list writer: Paste everything your team does and get a stop doing list: what to drop now, what needs notice, who to tell, and where the freed time goes.
  • Each item answered: would we start it today, and why
  • Stops sorted into now, with notice, and after replacing
  • Who tells whom, by when, with the sentence to use
  • The freed time or money and where it goes
• Product context file writer: Share product facts, audience and positioning. Get a reviewed context file that other marketing skills can reference.
  • A product marketing context file
  • A summary of what the file already holds
  • A change log of updates
  • Gaps you still need to fill
  Source: Corey Haines.
• Peter Drucker: Plan goals, team work or what to stop using Peter Drucker’s recorded approach. Start with the customer, useful results and people's strengths.
  • Your problem worked on the way Peter Drucker would: their questions, their method, their push-back
  • The answer or the work, in Peter Drucker's voice, using their ideas by name
  • Anything that goes beyond their public record, marked
  • One suggested next step

Tasks you can use it for

• Your backlog has 40 items and the team can do 8, and people are arguing about which.
• A stakeholder asks for one more thing mid-sprint, and you need to show what would drop out.
• Your sprints keep ending with half the work undone, and you suspect you are over-committing.
• You run a small product team and need a priority list you can defend to the boss or a client.

Limits to check before starting

• You are deciding whether to build one feature at all. Use the Product manager.
• You want a plan for a whole project with tasks and dates. Use the Project planning manager.
• You want to sort customer feedback into themes first. Use the Product feedback analyst.
• You need to track a test and decide what it proved. Use the Experiment tracker.

Best way to use this role

Give it one clear outcome, the actual files and a definition of done. Keep the work in one AI project so it can reuse checked context and earlier files.

• Download the pack from this page and add it to your AI as a skill. If you cannot, paste SKILL.md into a new chat, then paste references/source-agent.md.
• Paste the backlog, one item per line. Add team days, time off and the sprint goal. A spreadsheet export from Jira, Linear, Trello or Notion works.
• Add any numbers you trust, such as users affected or revenue at stake. Say which items you do not have numbers for.
• Read the ranked list and the line. Move any item the AI got wrong, and tell it why, then ask for a new ranking.
• Share the waiting list with the people who asked for those items before the sprint starts.

Read it as data

Read the complete role setup as JSON. Connect your AI to the AI Blocks MCP library and read aiblocks://roles/product-sprint-prioritizer for its role instructions and pinned sources.

This is a prepared AI role. No task has run. Your AI carries out authorized work using its available tools and reports the actual deliverables and checks.