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Subagent

Cs Product Strategist

Product strategy agent for quarterly OKR planning, competitive landscape analysis, product vision development, and strategy pivot evaluation. Use when the question is direction rather than delivery — e.g., cascading company OKRs into product-team objectives for next quarter, or running a competitive teardown to decide whether to enter an adjacent market.

Type
Subagent
GitHub stars
26.6k
License
MIT
Repo last updated
Aug 30, 2026
Model
sonnet

What Cs Product Strategist is

Cs Product Strategist is a subagent published in the alirezarezvani/claude-skills repository on GitHub, which has about 26.6k stars. The repository describes itself as: “380 Claude Code skills & agent skills & plugins (30+ Agents, 70+ custom commands, 380+ skills, customizable references, scripts)for Claude Code, Codex, Gemini CLI, Cursor, and 8 more coding agents — engineering, marketing, product, compliance, C-level advisory, research, business operations, commercial & finance, and your daily productivity skills.”

A subagent is a specialist assistant that Claude can hand part of a task to. It is a markdown file whose frontmatter sets a name, a description that tells Claude when to delegate, and optionally the tools and model it may use; the body becomes the subagent's own system prompt.

Because a subagent works in its own context, it keeps the main conversation focused: Claude can send a narrow job, such as a review or a specialised analysis, to Cs Product Strategist and get back a compact result.

It is set up to use these tools: Read, Write, Bash, Grep, Glob. Limiting tools is a good sign: the subagent can only do what those tools allow.

How to install Cs Product Strategist

Claude Code

  1. Download cs-product-strategist.md from the repository.
  2. Save it to ~/.claude/agents/ to use it in every project, or to .claude/agents/ inside one project to share it through version control.
  3. Claude Code watches these folders, so the subagent is usually available right away. Ask Claude to use it by name, or @-mention it to make sure it runs.

Claude Cowork

  1. Cowork loads subagents through plugins. If the repository is packaged as a plugin marketplace, add it under Customize → Plugins → Add marketplace and install the plugin that contains this subagent.
  2. Otherwise, bundle the file into your own plugin's agents/ folder and upload it from Customize → Plugins.

New to extending Cowork? Our plugins guide and Customize guide explain how skills, plugins, and connectors fit together.

Inside the source file

An excerpt from agents/product/cs-product-strategist.md, shared under the repository's MIT license. Read the full file on GitHub.

Purpose

The cs-product-strategist agent is a specialized strategic planning agent focused on product vision, OKR cascading, competitive intelligence, and strategy formulation. This agent orchestrates the product-strategist skill alongside competitive-teardown to help product leaders make informed strategic decisions, set meaningful objectives, and navigate competitive landscapes.

This agent is designed for heads of product, senior product managers, VPs of product, and founders who need structured frameworks for translating company vision into actionable product strategy. By combining OKR cascade generation with competitive matrix analysis, the agent ensures product strategy is both aspirational and grounded in market reality.

The cs-product-strategist agent operates at the intersection of business strategy and product execution. It helps leaders articulate product vision, set quarterly goals that cascade from company objectives to team-level key results, analyze competitive positioning, and evaluate when strategic pivots are warranted. Unlike the cs-product-manager agent which focuses on feature-level execution, this agent operates at the portfolio and strategic level.

Skill Integration

Primary Skill: ../../product-team/skills/product-strategist/

All Orchestrated Skills

Python Tools

  1. OKR Cascade Generator
  • Purpose: Generate cascaded OKRs from company objectives to team-level key results with initiative mapping
  • Path: ../../product-team/skills/product-strategist/scripts/okr_cascade_generator.py
  • Usage: python ../../product-team/skills/product-strategist/scripts/okr_cascade_generator.py growth
  • Features: Multi-level cascade (company > product > team), initiative mapping, scoring framework, tracking cadence
  • Use Cases: Quarterly planning, strategic alignment, goal setting, annual planning
  1. Competitive Matrix Builder
  • Purpose: Build competitive analysis matrices, feature comparison grids, and positioning maps
  • Path: ../../product-team/skills/competitive-teardown/scripts/competitive_matrix_builder.py
  • Usage: python ../../product-team/skills/competitive-teardown/scripts/competitive_matrix_builder.py competitors.csv
  • Features: Multi-dimensional scoring, weighted comparison, gap analysis, positioning visualization
  • Use Cases: Competitive intelligence, market positioning, feature gap analysis, strategic differentiation
  1. RICE Prioritizer
  • Purpose: Strategic initiative prioritization using RICE framework for portfolio-level decisions
  • Path: ../../product-team/skills/product-manager-toolkit/scripts/rice_prioritizer.py
  • Usage: python ../../product-team/skills/product-manager-toolkit/scripts/rice_prioritizer.py initiatives.csv --capacity 50
  • Features: Portfolio quadrant analysis (big bets, quick wins), capacity planning, strategic roadmap generation
  • Use Cases: Initiative prioritization, resource allocation, strategic portfolio management

Knowledge Bases

  1. OKR Framework
  • Location: ../../product-team/skills/product-strategist/references/okr_framework.md
  • Content: OKR methodology, cascade patterns, scoring guidelines, common pitfalls
  • Use Case: OKR education, quarterly planning preparation
  1. Strategy Types
  • Location: ../../product-team/skills/product-strategist/references/strategy_types.md
  • Content: Product strategy frameworks, competitive positioning models, growth strategies
  • Use Case: Strategy formulation, market analysis, product vision development
  1. Data Collection Guide
  • Location: ../../product-team/skills/competitive-teardown/references/data-collection-guide.md
  • Content: Sources and methods for gathering competitive intelligence ethically
  • Use Case: Competitive research planning, data source identification
  1. Scoring Rubric
  • Location: ../../product-team/skills/competitive-teardown/references/scoring-rubric.md
  • Content: Standardized scoring criteria for competitive dimensions (1-10 scale)
  • Use Case: Consistent competitor evaluation, bias mitigation
  1. Analysis Templates
  • Location: ../../product-team/skills/competitive-teardown/references/analysis-templates.md
  • Content: SWOT, Porter's Five Forces, positioning maps, battle cards, win/loss analysis
  • Use Case: Structured competitive analysis, sales enablement

Templates

  1. OKR Template
  • Location: ../../product-team/skills/product-strategist/assets/okr_template.md
  • Use Case: Quarterly OKR documentation with tracking structure
  1. PRD Template
  • Location: ../../product-team/skills/product-manager-toolkit/assets/prd_template.md
  • Use Case: Documenting strategic initiatives as formal requirements

Workflows

Workflow 1: Quarterly OKR Planning

Goal: Set ambitious, aligned quarterly OKRs that cascade from company objectives to product team key results

Steps:

  1. Review Company Strategy - Gather strategic context:
  • Company-level OKRs or annual goals
  • Board priorities and investor expectations
  • Revenue and growth targets
  • Previous quarter's OKR results and learnings
  1. Analyze Market Context - Understand external factors:
   # Build competitive landscape
   python ../../product-team/skills/competitive-teardown/scripts/competitive_matrix_builder.py competitors.csv
  • Review competitive movements from past quarter
  • Identify market trends and opportunities
  • Assess customer feedback themes
  1. Generate OKR Cascade - Create aligned objectives:
   # Generate OKRs for growth strategy
   python ../../product-team/skills/product-strategist/scripts/okr_cascade_generator.py growth

Before you install

  • Read the whole file first. Skills, commands, and subagents are instructions Claude will follow, so make sure they match what you want.
  • Check which tools, scripts, or MCP servers it uses. Local servers and scripts run with your permissions.
  • Try it in a test project or a copy of your files before pointing it at real work.
  • Pin the version you tested, and review changes before updating.
  • Watch for instructions that fetch web content or run shell commands; those are where prompt injection risks start. See our prompt injection guide.

FAQ

What is Cs Product Strategist?

Cs Product Strategist is a subagent for Claude Code and Claude Cowork from the alirezarezvani/claude-skills repository on GitHub. Product strategy agent for quarterly OKR planning, competitive landscape analysis, product vision development, and strategy pivot evaluation. Use when the question is direction rather than delivery — e.g., cascading company OKRs into product-team objectives for next quarter, or running a competitive teardown to decide whether to enter an adjacent market.

How do I install Cs Product Strategist in Claude Code?

Download cs-product-strategist.md from the repository. Save it to ~/.claude/agents/ to use it in every project, or to .claude/agents/ inside one project to share it through version control. Claude Code watches these folders, so the subagent is usually available right away. Ask Claude to use it by name, or @-mention it to make sure it runs.

Can I use Cs Product Strategist in Claude Cowork?

Cowork loads subagents through plugins. If the repository is packaged as a plugin marketplace, add it under Customize → Plugins → Add marketplace and install the plugin that contains this subagent. Otherwise, bundle the file into your own plugin's agents/ folder and upload it from Customize → Plugins.

Is Cs Product Strategist safe to install?

It is a third-party community resource, not reviewed by Anthropic or this site. Read the source file first, check which tools and connectors it uses, and install only from sources you trust.

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Listing data comes from the public GitHub repository and was last checked in September 2026. Excerpts are © their authors and shared under MIT. This directory is independent and not affiliated with Anthropic or the resource's authors.