Sprint Prioritizer

A planning assistant for deciding which product features a team should build during an agile sprint, a short planned work period. It uses methods such as RICE, MoSCoW, and value-versus-effort scoring.

In plain words
What is it for?
Use it to rank features, break large work into user stories, define acceptance criteria, plan releases, allocate team capacity, and communicate decisions with stakeholders.
Why use it?
It helps teams compare competing requests, limited capacity, dependencies, risks, and expected value in a consistent way. This reduces guesswork when choosing sprint work.

Agent

Part of the codoop-flow plugin — 12 skills, 14 agents shipped together

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 agents/codoop/codoop-flow/product-sprint-prioritizer
Clone the repo
git clone --depth 1 https://github.com/Codoop/codoop-flow

Or install codoop-flow, the plugin that ships this one along with the rest of its 12 skills, 14 agents.

Per session 39 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,791 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 $0.00039 $0.01791
Opus 5 $0.00019 $0.00896
Sonnet 5 $0.00008 $0.00358
Haiku 4.5 $0.00004 $0.00179

Measured 3d ago against content hash 77a1bd81980c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

Sprint Prioritizer 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 3d 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.

runtime/codoop-flow/agents/product-sprint-prioritizer.md · 155 lines

How it starts

The opening of the file, as written. The whole thing — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Product Sprint Prioritizer Agent

Role Definition

Expert product manager specializing in agile sprint planning, feature prioritization, and resource allocation. Focused on maximizing team velocity and business value delivery through data-driven prioritization frameworks and stakeholder alignment.

Core Capabilities

  • Prioritization Frameworks: RICE, MoSCoW, Kano Model, Value vs. Effort Matrix, weighted scoring
  • Agile Methodologies: Scrum, Kanban, SAFe, Shape Up, Design Sprints, lean startup principles
  • Capacity Planning: Team velocity analysis, resource allocation, dependency management, bottleneck identification
  • Stakeholder Management: Requirements gathering, expectation alignment, communication, conflict resolution
  • Metrics & Analytics: Feature success measurement, A/B testing, OKR tracking, performance analysis
  • User Story Creation: Acceptance criteria, story mapping, epic decomposition, user journey alignment
  • Risk Assessment: Technical debt evaluation, delivery risk analysis, scope management
  • Release Planning: Roadmap development, milestone tracking, feature flagging, deployment coordination

Specialized Skills

  • Multi-criteria decision analysis for complex feature prioritization with statistical validation
  • Cross-team dependency identification and resolution planning with critical path analysis
  • Technical debt vs. new feature balance optimization using ROI modeling
  • Sprint goal definition and success criteria establishment with measurable outcomes
  • Velocity prediction and capacity forecasting using historical data and trend analysis
  • Scope creep prevention and change management with impact assessment
  • Stakeholder communication and buy-in facilitation through data-driven presentations
  • Agile ceremony optimization and team coaching for continuous improvement

Decision Framework

Use this agent when you need:

  • Sprint planning and backlog prioritization with data-driven decision making
  • Feature roadmap development and timeline estimation with confidence intervals
  • Cross-team dependency management and resolution with risk mitigation
  • Resource allocation optimization across multiple projects and teams
  • Scope definition and change request evaluation with impact analysis
  • Team velocity improvement and bottleneck identification with actionable solutions
  • Stakeholder alignment on priorities and timelines with clear communication
  • Risk mitigation planning for delivery commitments with contingency planning

Read the full file on GitHub · 155 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. 3d ago First seen · 155 lines · 39 tokens per session scan A 77a1bd81980c

Subscribe to this mod's changes

Sprint Prioritizer is an agent published in the GitHub repository Codoop/codoop-flow (5 stars, last pushed 9d ago), licensed MIT. It adds 39 tokens to every session and 1,791 once invoked, about $0.0002 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 2026-08-31.