Triage assumptions using an Impact × Risk matrix and suggest targeted experiments.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionprioritize-assumptionsExecute the skills CLI command in your project's root directory to begin installation:
Fetches prioritize-assumptions from phuryn/pm-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate prioritize-assumptions. Access via /prioritize-assumptions in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
0
total installs
0
this week
9.5K
GitHub stars
0
upvotes
Run in your terminal
0
installs
0
this week
9.5K
stars
Triage assumptions using an Impact × Risk matrix and suggest targeted experiments.
You are helping prioritize assumptions for $ARGUMENTS.
If the user provides files with assumptions or research data, read them first.
ICE works well for assumption prioritization: Impact (Opportunity Score × # Customers) × Confidence (1–10) × Ease (1–10). Opportunity Score = Importance × (1 − Satisfaction), normalized to 0–1 (Dan Olsen). RICE splits Impact into Reach × Impact separately: (R × I × C) / E. See the prioritization-frameworks skill for full formulas and templates.
The user will provide a list of assumptions to prioritize. Apply the following framework:
For each assumption, evaluate two dimensions:
Categorize each assumption using the Impact × Risk matrix:
For each assumption requiring testing, suggest an experiment that:
Present results as a prioritized matrix or table.
Think step by step. Save as markdown if the output is substantial.
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
prioritize-assumptions reduced setup friction for our internal harness; good balance of opinion and flexibility.
Keeps context tight: prioritize-assumptions is the kind of skill you can hand to a new teammate without a long onboarding doc.
We added prioritize-assumptions from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: prioritize-assumptions is focused, and the summary matches what you get after install.
Registry listing for prioritize-assumptions matched our evaluation — installs cleanly and behaves as described in the markdown.
prioritize-assumptions is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Useful defaults in prioritize-assumptions — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
prioritize-assumptions fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
I recommend prioritize-assumptions for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
We added prioritize-assumptions from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
showing 1-10 of 67