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product-manager-toolkit

0.0
B

Comprehensive toolkit for product managers including RICE prioritization, customer interview analysis, PRD templates, discovery frameworks, and go-to-market strategies. Use for feature prioritization, user research synthesis, requirement documentation, and product strategy development.

Commands Agents Marketplace
#claude-ai#prioritization#claudecode-subagents#claude-ai-skills#RICE#customer interview#feature#features

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Installation for Agentic Skill

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skilz install alirezarezvani/claude-skills/product-manager-toolkit
skilz install alirezarezvani/claude-skills/product-manager-toolkit --agent opencode
skilz install alirezarezvani/claude-skills/product-manager-toolkit --agent codex
skilz install alirezarezvani/claude-skills/product-manager-toolkit --agent gemini

First time? Install Skilz: pip install skilz

Works with 22+ AI coding agents

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Extract and copy to ~/.claude/skills/ then restart Claude Desktop

1. Clone the repository:
git clone https://github.com/alirezarezvani/claude-skills
2. Copy the agent skill directory:
cp -r claude-skills/product-team/product-manager-toolkit ~/.claude/skills/

Need detailed installation help? Check our platform-specific guides:

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Agentic Skill Details

Repository
claude-skills
Type
Other
Meta-Domain
N/A
Primary Domain
N/A
Market Score
0.0

Agent Skill Grade

B
Score: 80/100 Click to see breakdown

Score Breakdown

Spec Compliance
12/15
PDA Architecture
22/30
Ease of Use
19/25
Writing Style
7/10
Utility
17/20
Modifiers: +3

Areas to Improve

  • SKILL.md is 352 lines without table of contents, violating PDA requirement for TOC in files >100 lines
  • SKILL.md contains 352 lines with extensive inline frameworks, metrics, and best practices that should be in references
  • Uses second-person 'your' instead of imperative/infinitive form in several places

Recommendations

  • Address 2 high-severity issues first
  • Add trigger phrases to description for discoverability
  • Add table of contents for files over 100 lines

Graded: 1/23/2026

Developer Feedback

I took a look at how you've structured the product-manager-toolkit skill—the way you've organized the mental models and frameworks for different PM scenarios is pretty thoughtful. What made you decide to go heavy on the decision-making frameworks rather than process templates?

Links:

The TL;DR

You're at 80/100, solid B territory. This is graded against Anthropic's best practices for token efficiency, ease of use, and practical utility. Your strongest area is Utility (17/20)—the RICE prioritizer and PRD tools actually solve real PM problems. Weakest area is Writing Style (7/10)—some verbose sections and inconsistent voice that's holding you back from the high 80s.

What's Working Well

  • Practical Python tools - The rice_prioritizer.py and prd_templates.md actually generate working output; not just theory
  • Clear trigger phrases - "RICE prioritization", "PRD", "customer interview" make it easy to know when to use this
  • Good framework scaffolding - RICE formula, MoSCoW, Opportunity Solution Tree are well-explained in context
  • Modular structure - References and scripts are cleanly separated from the main SKILL.md

The Big One: Missing TOC + Verbose SKILL.md

Your SKILL.md is 352 lines without a table of contents—that's a hard miss on Progressive Disclosure Architecture (PDA). More importantly, you're burying the lead. Half that content (RICE formula, MoSCoW definitions, customer interview guides, best practices) belongs in references/frameworks.md.

The fix: Add a TOC to SKILL.md, then move the detailed frameworks to a new reference file. Keep SKILL.md as the cockpit (overview + quick start), let references hold the manuals. This'll tighten your token usage and bump PDA from 22 to 25+.

Other Things Worth Fixing

  1. Second-person voice creeping in (lines 27, 104, 335) - You're saying "your PM tool" and "your environment" instead of imperative form. Stay consistent: "Integrates with..." not "Your toolkit integrates..."

  2. No input/output examples - Show what users will actually see. Add a concrete example: Input CSV with 3 features, output showing RICE scores and priority ranking. This is quick but high-impact for Utility.

  3. Incomplete feedback loops - Your workflows stop at "Generate Roadmap" but don't show validation. Add a "Check Results" step: compare against strategic goals, sensitivity analysis, stakeholder review → adjust → regenerate.

  4. Redundant framework sections - RICE is explained both in Core Workflows (lines 39-57) AND in a standalone section (lines 176-194). Pick one location, eliminate the duplicate.

Quick Wins

  • Add TOC to SKILL.md → +2 points (PDA)
  • Move frameworks to references/frameworks.md → +3 points (PDA)
  • Add input/output examples → +1 point (Utility)
  • Fix second-person voice → +1 point (Writing Style)
  • Consolidate duplicate framework definitions → +1 point (PDA)

That's realistically +8 points to hit 88/100 with minimal refactoring.


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AI-Detected Topics

Extracted using NLP analysis

claude-ai prioritization claudecode-subagents claude-ai-skills RICE customer interview feature features analysis claude-skills claude-code discovery customer feature prioritization PRD anthropic-claude claude-code-skills agentic-ai agentic-coding

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