Habilidades product-manager-toolkit

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product-manager-toolkit

Name: product-manager-toolkit
Author: sickn33

Seguro

Product Manager Toolkit

Também disponível em: alirezarezvani,davila7

A comprehensive toolkit for product managers to prioritize features using RICE scoring, analyze customer interviews, and create professional PRD documents. Streamlines product discovery and planning workflows.

Suporta: Claude Codex Code(CC)

🥉 73 Bronze

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A utilizar "product-manager-toolkit". Feature list: Login improvement (reach 5000, impact high, confidence 80%, effort 3), Search redesign (reach 10000, impact medium, confidence 90%, effort 5), Notification system (reach 2000, impact massive, confidence 60%, effort 8)

Resultado esperado:

RICE Scores:
1. Search Redesign: Score 180 (Reach 10000 × Impact 0.5 × Confidence 0.9 ÷ Effort 5)
2. Login Improvement: Score 133 (Reach 5000 × Impact 0.5 × Confidence 0.8 ÷ Effort 3)
3. Notification System: Score 30 (Reach 2000 × Impact 1.0 × Confidence 0.6 ÷ Effort 8)

Recommendation: Focus on Search Redesign and Login Improvement for Q1.

A utilizar "product-manager-toolkit". Customer said: 'The current dashboard is so slow, it takes forever to load. I really need real-time notifications when orders come in. The search function is useless - I can never find what I need. But I love the new reporting feature!'

Resultado esperado:

Pain Points (Severity: High):
- Slow dashboard loading
- Poor search functionality

Feature Requests (Priority: High):
- Real-time notifications for orders

Sentiment: Mixed (positive for reporting, negative for performance)

Key Quote: 'The current dashboard is so slow, it takes forever to load'

Auditoria de Segurança

Seguro

v1 • 2/24/2026

All 71 static findings evaluated as false positives. The skill contains legitimate Python CLI scripts for product management workflows. Documentation shows example commands in markdown code blocks (not actual execution). Market sizing references (TAM/SAM/SOM) were incorrectly flagged as Windows SAM. Generic terms triggered weak crypto flags. File operations are intentional CLI functionality for reading user-provided transcript files.

Arquivos analisados

1,414

Linhas analisadas

achados

Total de auditorias

Problemas de Alto Risco (6)

SKILL.md:15-353 references/prd_templates.md:65-270

False Positive: External Commands Flagged

Static scanner flagged markdown code blocks showing 'python scripts/...' as shell backtick execution. These are documentation examples, not actual command execution. Located in SKILL.md lines showing example CLI usage.

references/prd_templates.md:41-122 references/prd_templates.md:166-315 scripts/customer_interview_analyzer.py:74-283 scripts/rice_prioritizer.py:219-247 SKILL.md:3-356

False Positive: Weak Cryptographic Algorithm

Scanner incorrectly flagged common words like 'Security', 'Design', 'Principles', 'High-Level' as weak crypto algorithms. No cryptographic code exists in this skill.

references/prd_templates.md:27

False Positive: Windows SAM Database

Line 27 of prd_templates.md contains 'TAM, SAM, SOM' which refers to market sizing (Total Addressable Market, Serviceable Available Market, Serviceable Obtainable Market), not Windows Security Account Manager.

scripts/customer_interview_analyzer.py:116-281

False Positive: HTTP Client Library / Network Access

Scanner flagged 'requests.append()' as HTTP library usage. This is a Python list variable named 'requests' storing analysis results, not the HTTP requests library.

scripts/rice_prioritizer.py:288

False Positive: Certificate/Key Files

Scanner flagged 'keys = prioritized[0].keys()' as certificate keys. This is simply extracting dictionary keys for CSV output formatting.

scripts/customer_interview_analyzer.py:382 scripts/rice_prioritizer.py:240

Legitimate: File Input Operations

Scripts accept file paths from command line arguments to read user-provided transcript files. This is expected CLI tool behavior.

Auditado por: claude

Pontuação de qualidade

Arquitetura

100

Manutenibilidade

Conteúdo

Comunidade

Segurança

100

Conformidade com especificações

O Que Você Pode Construir

Feature Prioritization Workshop

Run a feature prioritization session using RICE scoring. Generate a CSV of features with scores, then use the script to rank and plan roadmap capacity.

Customer Interview Synthesis

After customer interviews, paste transcript into a text file and run the analyzer to extract actionable insights, sentiment, and feature requests.

PRD Documentation Creation

Use PRD templates to document new feature requirements. Choose from standard, one-page, or feature brief formats based on scope.

Tente Estes Prompts

Prioritize My Feature List

Use the RICE prioritization method to help me score these features. For each feature, I need to estimate: Reach (users per quarter), Impact (massive/high/medium/low/minimal), Confidence (high/medium/low), and Effort (person-months). Here's my feature list: [paste features]

Analyze Customer Interview

I have a customer interview transcript. Please analyze it and extract: 1) Key pain points with severity, 2) Explicit feature requests, 3) Sentiment (positive/negative/neutral), 4) Jobs to be done, 5) Key quotes. Here's the transcript: [paste transcript]

Draft PRD from Discovery

Help me create a Product Requirements Document for a new feature. I have these inputs: Problem statement [describe], Target users [define], Success metrics [list], Timeline [specify]. Please structure this as a standard PRD using the template format.

Capacity Planning for Quarter

I have 20 prioritized features with RICE scores and effort estimates. Our team has capacity for 15 person-months this quarter. Which features should we commit to? Show me the portfolio breakdown of quick wins vs big bets.

Melhores Práticas

Gather cross-functional input when scoring RICE components to improve accuracy
Use customer interview analysis to validate pain points before prioritizing solutions
Start with one-page PRD for small features, use standard PRD for complex initiatives
Review and update RICE scores quarterly as confidence and reach data improves

Evitar

Do not skip confidence scoring - it prevents overconfidence in uncertain estimates
Do not use RICE for all decisions - combine with strategic fit and technical dependencies
Do not write PRDs without user research - validate problems first
Do not ignore effort estimates from engineering - use realistic team velocity

Perguntas Frequentes

What is RICE prioritization?

RICE is a scoring framework: Reach (users affected) × Impact (effect on user) × Confidence ( certainty of estimates) ÷ Effort (resources needed). Higher scores indicate higher priority.

Do I need to install any dependencies?

The scripts require Python 3.6 or higher. No external packages needed - they use only standard library modules.

Can I use this with Claude Code or Codex?

Yes. The toolkit works as a CLI companion. You can use Claude to draft features and PRDs, then run the Python scripts for numerical scoring and analysis.

How do I estimate Reach for a feature?

Reach = number of users who will benefit per quarter. For existing features, use analytics data. For new features, estimate based on user research and market size.

What file formats does the interview analyzer accept?

The script reads plain text (.txt) files. Paste your interview transcript into a text file and pass it as a command line argument.

Can I export results to JSON or CSV?

Yes. The rice_prioritizer.py supports --output json or csv flags. Default output is to console for easy copying.