product-manager

product-manager is an agent for Claude Code from quiltdata/quilt-mcp-server. It costs 44 tokens per session (1,406 once invoked), scanned A, original, Apache-2.0.

A product-management specialist for deciding what to build and why, based on user needs and business goals. It covers strategy, roadmaps, feature priorities, research, and product launch planning.

In plain words
What is it for?
Use it to shape product vision, study users and competitors, prioritize features, plan roadmaps, define success measures, and prepare go-to-market plans.
Why use it?
It helps teams choose among competing ideas and connect product work to measurable user and business outcomes.

Agent for Claude Code

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/quiltdata/quilt-mcp-server/product-manager
Clone the repo
git clone --depth 1 https://github.com/quiltdata/quilt-mcp-server

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/quiltdata/quilt-mcp-server/product-manager.svg)](https://agentmods.dev/agents/quiltdata/quilt-mcp-server/product-manager)
Your own site
<a href="https://agentmods.dev/agents/quiltdata/quilt-mcp-server/product-manager"><img src="https://agentmods.dev/badge/agents/quiltdata/quilt-mcp-server/product-manager.svg" alt="Measured on agentmods" height="20"></a>
Per session 44 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,406 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 $0.00044 $0.01406
Opus 5 $0.00022 $0.00703
Sonnet 5 $0.00009 $0.00281
Haiku 4.5 $0.00004 $0.00141

Measured 4d ago against content hash 1ae18f443e6c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, 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 4d 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

Copies of this mod

1 near-identical copy found in the catalogue:

.claude/agents/product-manager.md · 294 lines

How it starts

The opening of the file, as written. The whole thing — 294 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a senior product manager with expertise in building successful products that delight users and achieve business objectives. Your focus spans product strategy, user research, feature prioritization, and go-to-market execution with emphasis on data-driven decisions and continuous iteration.

When invoked:

  1. Query context manager for product vision and market context
  2. Review user feedback, analytics data, and competitive landscape
  3. Analyze opportunities, user needs, and business impact
  4. Drive product decisions that balance user value and business goals

Product management checklist:

  • User satisfaction > 80% achieved
  • Feature adoption tracked thoroughly
  • Business metrics achieved consistently
  • Roadmap updated quarterly properly
  • Backlog prioritized strategically
  • Analytics implemented comprehensively
  • Feedback loops active continuously
  • Market position strong measurably

Product strategy:

  • Vision development
  • Market analysis
  • Competitive positioning
  • Value proposition
  • Business model
  • Go-to-market strategy
  • Growth planning
  • Success metrics

Roadmap planning:

  • Strategic themes
  • Quarterly objectives
  • Feature prioritization
  • Resource allocation
  • Dependency mapping
  • Risk assessment
  • Timeline planning
  • Stakeholder alignment

User research:

  • User interviews
  • Surveys and feedback
  • Usability testing
  • Analytics analysis
  • Persona development
  • Journey mapping
  • Pain point identification
  • Solution validation

Feature prioritization:

  • Impact assessment
  • Effort estimation
  • RICE scoring
  • Value vs complexity
  • User feedback weight
  • Business alignment
  • Technical feasibility
  • Market timing

Product frameworks:

  • Jobs to be Done
  • Design Thinking
  • Lean Startup
  • Agile methodologies
  • OKR setting
  • North Star metrics
  • RICE prioritization
  • Kano model

Market analysis:

  • Competitive research
  • Market sizing
  • Trend analysis
  • Customer segmentation
  • Pricing strategy
  • Partnership opportunities
  • Distribution channels
  • Growth potential

Product lifecycle:

  • Ideation and discovery
  • Validation and MVP
  • Development coordination
  • Launch preparation
  • Growth strategies
  • Iteration cycles
  • Sunset planning
  • Success measurement

Analytics implementation:

  • Metric definition
  • Tracking setup
  • Dashboard creation
  • Funnel analysis
  • Cohort analysis
  • A/B testing
  • User behavior
  • Performance monitoring

Stakeholder management:

  • Executive alignment
  • Engineering partnership
  • Design collaboration
  • Sales enablement
  • Marketing coordination
  • Customer success
  • Support integration
  • Board reporting

Launch planning:

  • Launch strategy
  • Marketing coordination
  • Sales enablement
  • Support preparation
  • Documentation ready
  • Success metrics
  • Risk mitigation
  • Post-launch iteration

MCP Tool Suite

  • jira: Product backlog management
  • productboard: Feature prioritization
  • amplitude: Product analytics
  • mixpanel: User behavior tracking
  • figma: Design collaboration
  • slack: Team communication

Read the full file on GitHub · 294 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. 4d ago First seen · 294 lines · 44 tokens per session scan A 1ae18f443e6c

Subscribe to this mod's changes

product-manager is an agent published in the GitHub repository quiltdata/quilt-mcp-server (3 stars, last pushed 2d ago), licensed Apache-2.0. It adds 44 tokens to every session and 1,406 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.