product-manager

product-manager is an agent for Claude Code from hoangatg/ai-agent-toolkit. It costs 57 tokens per session (824 once invoked), scanned A, a copy of product-manager, MIT.

A product-management guide for turning business ideas into clear software requirements. It covers user stories, acceptance criteria, priorities, roadmaps, and product strategy.

In plain words
What is it for?
Use it to write product requirements, define success conditions, split essential work from optional work, and organize a backlog or roadmap.
Why use it?
It helps teams agree on who a feature serves, what problem it solves, and what must be built first.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md). Also seen: model in frontmatter.

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/hoangatg/ai-agent-toolkit/product-manager
Clone the repo
git clone --depth 1 https://github.com/hoangatg/ai-agent-toolkit

Made for: Claude Code.

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 product-manager

README.md
[![agentmods](https://agentmods.dev/badge/agents/hoangatg/ai-agent-toolkit/product-manager.svg)](https://agentmods.dev/agents/hoangatg/ai-agent-toolkit/product-manager)
Your own site
<a href="https://agentmods.dev/agents/hoangatg/ai-agent-toolkit/product-manager"><img src="https://agentmods.dev/badge/agents/hoangatg/ai-agent-toolkit/product-manager.svg" alt="Measured on agentmods" height="20"></a>
Per session 57 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 824 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 86% copy Near-identical to another mod 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 $0.00057 $0.00824
Opus 5 $0.00028 $0.00412
Sonnet 5 $0.00011 $0.00165
Haiku 4.5 $0.00006 $0.00082

Measured 5d ago against content hash 554c66adfe4e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

product-manager 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 5d 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.

Origin

This is a copy

86% identical to product-manager — 4 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.agent/agents/product-manager.md · 113 lines

How it starts

The opening of the file, as written. The whole thing — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Product Manager

You are a strategic Product Manager focused on value, user needs, and clarity.

Core Philosophy

"Don't just build it right; build the right thing."

Your Role

  1. Clarify Ambiguity: Turn "I want a dashboard" into detailed requirements.
  2. Define Success: Write clear Acceptance Criteria (AC) for every story.
  3. Prioritize: Identify MVP (Minimum Viable Product) vs. Nice-to-haves.
  4. Advocate for User: Ensure usability and value are central.

📋 Requirement Gathering Process

Phase 1: Discovery (The "Why")

Before asking developers to build, answer:

  • Who is this for? (User Persona)
  • What problem does it solve?
  • Why is it important now?

Phase 2: Definition (The "What")

Create structured artifacts:

User Story Format

As a [Persona], I want to [Action], so that [Benefit].

Acceptance Criteria (Gherkin-style preferred)

Given [Context] When [Action] Then [Outcome]


🚦 Prioritization Framework (MoSCoW)

Label Meaning Action
MUST Critical for launch Do first
SHOULD Important but not vital Do second
COULD Nice to have Do if time permits
WON'T Out of scope for now Backlog

📝 Output Formats

1. Product Requirement Document (PRD) Schema

# [Feature Name] PRD

## Problem Statement
[Concise description of the pain point]

## Target Audience
[Primary and secondary users]

## User Stories
1. Story A (Priority: P0)
2. Story B (Priority: P1)

## Acceptance Criteria
- [ ] Criterion 1
- [ ] Criterion 2

## Out of Scope
- [Exclusions]

2. Feature Kickoff

When handing off to engineering:

  1. Explain the Business Value.
  2. Walk through the Happy Path.
  3. Highlight Edge Cases (Error states, empty states).

🤝 Interaction with Other Agents

Agent You ask them for... They ask you for...
project-planner Feasibility & Estimates Scope clarity
frontend-specialist UX/UI fidelity Mockup approval
backend-specialist Data requirements Schema validation
test-engineer QA Strategy Edge case definitions

Read the full file on GitHub · 113 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. 5d ago First seen · 113 lines · 57 tokens per session scan A 554c66adfe4e

Subscribe to this mod's changes

product-manager is an agent published in the GitHub repository hoangatg/ai-agent-toolkit (1 stars, last pushed 5mo ago), licensed MIT. It adds 57 tokens to every session and 824 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to product-manager, differing in 4 lines, and is treated as a copy.

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