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Agent skill

Product Manager Toolkit

by davila7 in davila7/claude-code-templates

Scores feature requests with RICE, mines customer interview transcripts for pain points, and offers PRD templates, with two Python scripts behind it.

MITAuto-check passedProduct & Project Management

Install Product Manager Toolkit

skills CLI
$ npx skills add davila7/claude-code-templates --skill product-manager-toolkit -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install davila7/claude-code-templates product-manager-toolkit --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/davila7/claude-code-templates.git skills-src && mkdir -p .claude/skills && cp -r skills-src/cli-tool/components/skills/business-marketing/product-manager-toolkit .claude/skills/product-manager-toolkit && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
product-manager-toolkit
GitHub stars
33k
Used in
7 other repos
Token cost
~2.2k tokens
SKILL.md length
691 words
Files
4 (incl. scripts, references)
Skills in repo
479
Repo updated
First seen
Licence
MIT

At a glance

Scores feature requests with RICE, mines customer interview transcripts for pain points, and offers PRD templates, with two Python scripts behind it.

  • Works in 4 steps: Choose template from… → Fill in sections based on discovery work → Review with stakeholders → …
  • Ranking a backlog of feature requests by reach, impact, confidence and effort
  • SKILL.md covers Quick Start, Core Workflows, Key Scripts and Reference Documents, plus 4 more sections
  • Runs Python scripts from its folder; calls python

What it does

The skill packages three product-management workflows. For prioritization, `scripts/rice_prioritizer.py` reads a CSV of features with reach, impact, confidence and effort columns, scores each one with RICE and accepts a `--capacity` value for planning a quarter; a sample mode writes a starter CSV. For discovery, `scripts/customer_interview_analyzer.py` processes an interview transcript and extracts pain points with severity, feature requests, jobs to be done, sentiment and recurring themes.

For requirement documents, `references/prd_templates.md` holds a standard PRD for complex features, a one-page PRD, a feature brief and an agile epic. The workflow advises ordering content as problem, solution and success metrics, always stating what is out of scope. Discovery frameworks and go-to-market strategy are named as further topics in the description, but the excerpt focuses on prioritization, interviews and PRDs.

When your agent uses it

  • Ranking a backlog of feature requests by reach, impact, confidence and effort
  • Turning interview transcripts into pain points and feature requests
  • Drafting a PRD or feature brief from discovery notes

Example prompts

  • “Score the features in features.csv with RICE and show what fits a capacity of 15.”
  • “Analyze interview_transcript.txt and list the pain points with their severity.”
  • “Write a one-page PRD for the bulk export feature, including what is out of scope.”

Requirements

  • Python to run the bundled scripts

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Choose template from references/prd_templates.md
  2. Fill in sections based on discovery work
  3. Review with stakeholders
  4. Version control in your PM tool

What it can do on your machine

Read from SKILL.md and the folder at commit c0ca7da. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Product Manager Toolkit loads about 2.2k tokens when it runs, and up to ~4k if it reads all its reference files. Until then it costs about 78 tokens; SKILL.md has 691 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~78
When it runs · the whole SKILL.md, loaded when a task matches
~2.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from davila7/claude-code-templates at commit c0ca7da, republished under its MIT licence (© davila7). 691 words, ~2,218 tokens.

Download SKILL.mdSave it as .claude/skills/product-manager-toolkit/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
product-manager-toolkit
description
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.

Product Manager Toolkit

Essential tools and frameworks for modern product management, from discovery to delivery.

Quick Start

For Feature Prioritization
bash
python scripts/rice_prioritizer.py sample  # Create sample CSV
python scripts/rice_prioritizer.py sample_features.csv --capacity 15
For Interview Analysis
bash
python scripts/customer_interview_analyzer.py interview_transcript.txt
For PRD Creation
  1. Choose template from references/prd_templates.md
  2. Fill in sections based on discovery work
  3. Review with stakeholders
  4. Version control in your PM tool

Core Workflows

Feature Prioritization Process

  1. Gather Feature Requests

    • Customer feedback
    • Sales requests
    • Technical debt
    • Strategic initiatives

  2. Score with RICE

    bash
    # Create CSV with: name,reach,impact,confidence,effort
python scripts/rice_prioritizer.py features.csv
    • Reach: Users affected per quarter
    • Impact: massive/high/medium/low/minimal
    • Confidence: high/medium/low
    • Effort: xl/l/m/s/xs (person-months)

  3. Analyze Portfolio

    • Review quick wins vs big bets
    • Check effort distribution
    • Validate against strategy

  4. Generate Roadmap

    • Quarterly capacity planning
    • Dependency mapping
    • Stakeholder alignment
Customer Discovery Process

  1. Conduct Interviews

    • Use semi-structured format
    • Focus on problems, not solutions
    • Record with permission

  2. Analyze Insights

    bash
    python scripts/customer_interview_analyzer.py transcript.txt

    Extracts:

    • Pain points with severity
    • Feature requests with priority
    • Jobs to be done
    • Sentiment analysis
    • Key themes and quotes

  3. Synthesize Findings

    • Group similar pain points
    • Identify patterns across interviews
    • Map to opportunity areas

  4. Validate Solutions

    • Create solution hypotheses
    • Test with prototypes
    • Measure actual vs expected behavior
PRD Development Process

  1. Choose Template

    • Standard PRD: Complex features (6-8 weeks)
    • One-Page PRD: Simple features (2-4 weeks)
    • Feature Brief: Exploration phase (1 week)
    • Agile Epic: Sprint-based delivery

  2. Structure Content

    • Problem → Solution → Success Metrics
    • Always include out-of-scope
    • Clear acceptance criteria

  3. Collaborate

    • Engineering for feasibility
    • Design for experience
    • Sales for market validation
    • Support for operational impact

Key Scripts

rice_prioritizer.py

Advanced RICE framework implementation with portfolio analysis.

Features:

  • RICE score calculation
  • Portfolio balance analysis (quick wins vs big bets)
  • Quarterly roadmap generation
  • Team capacity planning
  • Multiple output formats (text/json/csv)

Usage Examples:

bash
# Basic prioritization
python scripts/rice_prioritizer.py features.csv

# With custom team capacity (person-months per quarter)
python scripts/rice_prioritizer.py features.csv --capacity 20

# Output as JSON for integration
python scripts/rice_prioritizer.py features.csv --output json
customer_interview_analyzer.py

NLP-based interview analysis for extracting actionable insights.

Capabilities:

  • Pain point extraction with severity assessment
  • Feature request identification and classification
  • Jobs-to-be-done pattern recognition
  • Sentiment analysis
  • Theme extraction
  • Competitor mentions
  • Key quotes identification

Usage Examples:

bash
# Analyze single interview
python scripts/customer_interview_analyzer.py interview.txt

# Output as JSON for aggregation
python scripts/customer_interview_analyzer.py interview.txt json

Reference Documents

prd_templates.md

Multiple PRD formats for different contexts:

  1. Standard PRD Template

    • Comprehensive 11-section format
    • Best for major features
    • Includes technical specs

  2. One-Page PRD

    • Concise format for quick alignment
    • Focus on problem/solution/metrics
    • Good for smaller features

  3. Agile Epic Template

    • Sprint-based delivery
    • User story mapping
    • Acceptance criteria focus

  4. Feature Brief

    • Lightweight exploration
    • Hypothesis-driven
    • Pre-PRD phase

Prioritization Frameworks

RICE Framework
Score = (Reach × Impact × Confidence) / Effort

Reach: # of users/quarter
Impact: 
  - Massive = 3x
  - High = 2x
  - Medium = 1x
  - Low = 0.5x
  - Minimal = 0.25x
Confidence:
  - High = 100%
  - Medium = 80%
  - Low = 50%
Effort: Person-months
Value vs Effort Matrix
         Low Effort    High Effort
         
High     QUICK WINS    BIG BETS
Value    [Prioritize]   [Strategic]
         
Low      FILL-INS      TIME SINKS
Value    [Maybe]       [Avoid]
MoSCoW Method
  • Must Have: Critical for launch
  • Should Have: Important but not critical
  • Could Have: Nice to have
  • Won't Have: Out of scope

Discovery Frameworks

Customer Interview Guide
1. Context Questions (5 min)
   - Role and responsibilities
   - Current workflow
   - Tools used

2. Problem Exploration (15 min)
   - Pain points
   - Frequency and impact
   - Current workarounds

3. Solution Validation (10 min)
   - Reaction to concepts
   - Value perception
   - Willingness to pay

4. Wrap-up (5 min)
   - Other thoughts
   - Referrals
   - Follow-up permission
Hypothesis Template
We believe that [building this feature]
For [these users]
Will [achieve this outcome]
We'll know we're right when [metric]
Opportunity Solution Tree
Outcome
├── Opportunity 1
│   ├── Solution A
│   └── Solution B
└── Opportunity 2
    ├── Solution C
    └── Solution D

Metrics & Analytics

Show full SKILL.md (289 more words)Show less
North Star Metric Framework
  1. Identify Core Value: What's the #1 value to users?
  2. Make it Measurable: Quantifiable and trackable
  3. Ensure It's Actionable: Teams can influence it
  4. Check Leading Indicator: Predicts business success
Funnel Analysis Template
Acquisition → Activation → Retention → Revenue → Referral

Key Metrics:
- Conversion rate at each step
- Drop-off points
- Time between steps
- Cohort variations
Feature Success Metrics
  • Adoption: % of users using feature
  • Frequency: Usage per user per time period
  • Depth: % of feature capability used
  • Retention: Continued usage over time
  • Satisfaction: NPS/CSAT for feature

Best Practices

Writing Great PRDs
  1. Start with the problem, not solution
  2. Include clear success metrics upfront
  3. Explicitly state what's out of scope
  4. Use visuals (wireframes, flows)
  5. Keep technical details in appendix
  6. Version control changes
Effective Prioritization
  1. Mix quick wins with strategic bets
  2. Consider opportunity cost
  3. Account for dependencies
  4. Buffer for unexpected work (20%)
  5. Revisit quarterly
  6. Communicate decisions clearly
Customer Discovery Tips
  1. Ask "why" 5 times
  2. Focus on past behavior, not future intentions
  3. Avoid leading questions
  4. Interview in their environment
  5. Look for emotional reactions
  6. Validate with data
Stakeholder Management
  1. Identify RACI for decisions
  2. Regular async updates
  3. Demo over documentation
  4. Address concerns early
  5. Celebrate wins publicly
  6. Learn from failures openly

Common Pitfalls to Avoid

  1. Solution-First Thinking: Jumping to features before understanding problems
  2. Analysis Paralysis: Over-researching without shipping
  3. Feature Factory: Shipping features without measuring impact
  4. Ignoring Technical Debt: Not allocating time for platform health
  5. Stakeholder Surprise: Not communicating early and often
  6. Metric Theater: Optimizing vanity metrics over real value

Integration Points

This toolkit integrates with:

  • Analytics: Amplitude, Mixpanel, Google Analytics
  • Roadmapping: ProductBoard, Aha!, Roadmunk
  • Design: Figma, Sketch, Miro
  • Development: Jira, Linear, GitHub
  • Research: Dovetail, UserVoice, Pendo
  • Communication: Slack, Notion, Confluence

Quick Commands Cheat Sheet

bash
# Prioritization
python scripts/rice_prioritizer.py features.csv --capacity 15

# Interview Analysis
python scripts/customer_interview_analyzer.py interview.txt

# Create sample data
python scripts/rice_prioritizer.py sample

# JSON outputs for integration
python scripts/rice_prioritizer.py features.csv --output json
python scripts/customer_interview_analyzer.py interview.txt json

© davila7, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts, references) in cli-tool/components/skills/business-marketing/product-manager-toolkit of davila7/claude-code-templates.

  • SKILL.md
  • references/prd_templates.md
  • scripts/customer_interview_analyzer.py
  • scripts/rice_prioritizer.py

Open the folder on GitHubat commit c0ca7da

Used in 7 other repositories

We found 11 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 7 other GitHub owners. This page covers the copy in davila7/claude-code-templates, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Product Manager Toolkit next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Product Manager Toolkit compared with similar skills
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Product Manager Toolkit this skilldavila7/claude-code-templates33k7 repos~2.2kAutomated safety check: PassMIT
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Product Manager Toolkitborghei/Claude-Skills891—~5.8kAutomated safety check: PassMIT
Produck Feedback To Buildtryproduck/produck-skills511—~1kAutomated safety check: PassApache-2.0
Discovery Synthesisandreaskelm/pm-brain234—~2.3kAutomated safety check: PassCustom licence
User ResearchTechNomadCode/AI-Product-Development-Toolkit1k—~266Automated safety check: PassMIT

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Works with

Categories

Questions about Product Manager Toolkit

What does Product Manager Toolkit do?

Scores feature requests with RICE, mines customer interview transcripts for pain points, and offers PRD templates, with two Python scripts behind it. The skill packages three product-management workflows.py` reads a CSV of features with reach, impact, confidence and effort columns, scores each one with RICE and accepts a `--capacity` value for planning a quarter; a sample mode writes a starter CSV.

When should I use Product Manager Toolkit?

Product Manager Toolkit fits situations like: ranking a backlog of feature requests by reach, impact, confidence and effort; turning interview transcripts into pain points and feature requests; drafting a PRD or feature brief from discovery notes.

How do I install Product Manager Toolkit in Claude Code?

Run `npx skills add davila7/claude-code-templates --skill product-manager-toolkit -a claude-code`. Or copy the skill folder (cli-tool/components/skills/business-marketing/product-manager-toolkit in davila7/claude-code-templates) into .claude/skills/product-manager-toolkit in your project. Claude Code loads it when a task matches its description.

How do I install Product Manager Toolkit in Codex?

Run `npx skills add davila7/claude-code-templates --skill product-manager-toolkit -a codex`. Or copy the skill folder (cli-tool/components/skills/business-marketing/product-manager-toolkit in davila7/claude-code-templates) into .agents/skills/product-manager-toolkit in your project. Codex loads it when a task matches its description.

Can I use Product Manager Toolkit in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add davila7/claude-code-templates --skill product-manager-toolkit -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/product-manager-toolkit, .gemini/skills/product-manager-toolkit, .github/skills/product-manager-toolkit and .opencode/skills/product-manager-toolkit in your project.

What does Product Manager Toolkit need to run?

Going by SKILL.md and its folder, Product Manager Toolkit needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python to run the bundled scripts.

Does Product Manager Toolkit access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Product Manager Toolkit safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Product Manager Toolkit use?

Product Manager Toolkit is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Product Manager Toolkit use?

About 2.2k tokens (SKILL.md is roughly 8.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.8k tokens, read only when the agent opens those files.

What are the alternatives to Product Manager Toolkit?

Skills that share tags, products or a category with Product Manager Toolkit: Product Manager Toolkit (majiayu000/spellbook, 287 stars), Product Manager Toolkit (borghei/Claude-Skills, 891 stars), Produck Feedback To Build (tryproduck/produck-skills, 511 stars) and Discovery Synthesis (andreaskelm/pm-brain, 234 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Product Manager Toolkit?

davila7 (a GitHub user) maintains it in davila7/claude-code-templates, which has 32,512 GitHub stars. The repository holds 479 skills in this directory. The repository was last updated on October 10, 2026.

Source: davila7/claude-code-templates on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.