Product Manager Toolkit workflow skill. Use this skill when the user needs Essential tools and frameworks for modern product management, from discovery to delivery and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
Product Manager Toolkit workflow skill. Use this skill when the user needs Essential tools and frameworks for modern product management, from discovery to delivery and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
This public intake copy packages plugins/antigravity-bundle-startup-founder/skills/product-manager-toolkit from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.
Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.
This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.
Product Manager Toolkit Essential tools and frameworks for modern product management, from discovery to delivery.
Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Key Scripts, Prioritization Frameworks, Discovery Frameworks, Metrics & Analytics, Common Pitfalls to Avoid, Integration Points.
When to Use This Skill
Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.
This skill is applicable to execute the workflow or actions described in the overview.
Use when the request clearly matches the imported source intent: Essential tools and frameworks for modern product management, from discovery to delivery.
Use when the operator should preserve upstream workflow detail instead of rewriting the process from scratch.
Use when provenance needs to stay visible in the answer, PR, or review packet.
Use when copied upstream references, examples, or scripts materially improve the answer.
Use when the workflow should remain reviewable in the public intake repo before the private enhancer takes over.
Operating Table
Situation
Start here
Why it matters
First-time use
metadata.json
Confirms repository, branch, commit, and imported path through the external_source block before touching the copied workflow
Provenance review
ORIGIN.md
Gives reviewers a plain-language audit trail for the imported source
Workflow execution
references/prd_templates.md
Starts with the smallest copied file that materially changes execution
Supporting context
scripts/customer_interview_analyzer.py
Adds the next most relevant copied source file without loading the entire package
Handoff decision
## Related Skills
Helps the operator switch to a stronger native skill when the task drifts
Workflow
This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.
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:
# 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:
# 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
Examples
Example 1: Ask for the upstream workflow directly
Use @product-manager-toolkit-v3 to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.
Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.
Example 2: Ask for a provenance-grounded review
Review @product-manager-toolkit-v3 against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.
Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.
Example 3: Narrow the copied support files before execution
Use @product-manager-toolkit-v3 for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.
Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.
Example 4: Build a reviewer packet
Review @product-manager-toolkit-v3 using the copied upstream files plus provenance, then summarize any gaps before merge.
Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.
Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.
Start with the problem, not solution
Include clear success metrics upfront
Explicitly state what's out of scope
Use visuals (wireframes, flows)
Keep technical details in appendix
Version control changes
Mix quick wins with strategic bets
Imported Operating Notes
Imported: Best Practices
Writing Great PRDs
Start with the problem, not solution
Include clear success metrics upfront
Explicitly state what's out of scope
Use visuals (wireframes, flows)
Keep technical details in appendix
Version control changes
Effective Prioritization
Mix quick wins with strategic bets
Consider opportunity cost
Account for dependencies
Buffer for unexpected work (20%)
Revisit quarterly
Communicate decisions clearly
Customer Discovery Tips
Ask "why" 5 times
Focus on past behavior, not future intentions
Avoid leading questions
Interview in their environment
Look for emotional reactions
Validate with data
Stakeholder Management
Identify RACI for decisions
Regular async updates
Demo over documentation
Address concerns early
Celebrate wins publicly
Learn from failures openly
Troubleshooting
Problem: The operator skipped the imported context and answered too generically
Symptoms: The result ignores the upstream workflow in plugins/antigravity-bundle-startup-founder/skills/product-manager-toolkit, fails to mention provenance, or does not use any copied source files at all.
Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Check the external_source block first, then restate the provenance before continuing.
Problem: The imported workflow feels incomplete during review
Symptoms: Reviewers can see the generated SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task.
Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.
Problem: The task drifted into a different specialization
Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better.
Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.
Related Skills
@competitive-landscape-v3 - Use when the work is better handled by that native specialization after this imported skill establishes context.
@competitor-alternatives-v3 - Use when the work is better handled by that native specialization after this imported skill establishes context.
@copywriting-v3 - Use when the work is better handled by that native specialization after this imported skill establishes context.
@cpp-pro-v3 - Use when the work is better handled by that native specialization after this imported skill establishes context.
Additional Resources
Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.
Resource family
What it gives the reviewer
Example path
references
copied reference notes, guides, or background material from upstream
references/prd_templates.md
examples
worked examples or reusable prompts copied from upstream
examples/n/a
scripts
upstream helper scripts that change execution or validation
scripts/customer_interview_analyzer.py
agents
routing or delegation notes that are genuinely part of the imported package
agents/n/a
assets
supporting assets or schemas copied from the source package
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
Imported: 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
Imported: Metrics & Analytics
North Star Metric Framework
Identify Core Value: What's the #1 value to users?
Make it Measurable: Quantifiable and trackable
Ensure It's Actionable: Teams can influence it
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
Imported: Common Pitfalls to Avoid
Solution-First Thinking: Jumping to features before understanding problems
Analysis Paralysis: Over-researching without shipping
Feature Factory: Shipping features without measuring impact
Ignoring Technical Debt: Not allocating time for platform health
Stakeholder Surprise: Not communicating early and often
Metric Theater: Optimizing vanity metrics over real value
Imported: 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
Imported: Limitations
Use this skill only when the task clearly matches the scope described above.
Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
