Agent skill / mattpocock
Turn the current conversation context into a PRD and submit it as a GitHub issue.
Core file
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionto-prdExecute the skills CLI command in your project's root directory to begin installation:
Package manager
npx skills add https://github.com/mattpocock/skills/blob/main/to-prd/SKILL.md --skill to-prdFetches to-prd from mattpocock/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 to-prd. Access via /to-prdin 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.
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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
Copy the command for your terminal
Package manager
npx skills add https://github.com/mattpocock/skills/blob/main/to-prd/SKILL.md --skill to-prdWorks with
| name | to-prd |
| description | Turn the current conversation context into a PRD and submit it as a GitHub issue. Use when user wants to create a PRD from the current context. |
This skill takes the current conversation context and codebase understanding and produces a PRD. Do NOT interview the user — just synthesize what you already know.
Explore the repo to understand the current state of the codebase, if you haven't already.
Sketch out the major modules you will need to build or modify to complete the implementation. Actively look for opportunities to extract deep modules that can be tested in isolation.
A deep module (as opposed to a shallow module) is one which encapsulates a lot of functionality in a simple, testable interface which rarely changes.
Check with the user that these modules match their expectations. Check with the user which modules they want tests written for.
The problem that the user is facing, from the user's perspective.
The solution to the problem, from the user's perspective.
A LONG, numbered list of user stories. Each user story should be in the format of:
This list of user stories should be extremely extensive and cover all aspects of the feature.
A list of implementation decisions that were made. This can include:
Do NOT include specific file paths or code snippets. They may end up being outdated very quickly.
A list of testing decisions that were made. Include:
A description of the things that are out of scope for this PRD.
Any further notes about the feature.
</prd-template>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
mattpocock/skills
mattpocock/skills
mattpocock/skills
mattpocock/skills
garrytan/gstack
Solid pick for teams standardizing on skills: to-prd is focused, and the summary matches what you get after install.
Registry listing for to-prd matched our evaluation — installs cleanly and behaves as described in the markdown.
I recommend to-prd for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
to-prd has been reliable in day-to-day use. Documentation quality is above average for community skills.
to-prd reduced setup friction for our internal harness; good balance of opinion and flexibility.
to-prd is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Keeps context tight: to-prd is the kind of skill you can hand to a new teammate without a long onboarding doc.
Registry listing for to-prd matched our evaluation — installs cleanly and behaves as described in the markdown.
Useful defaults in to-prd — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend to-prd for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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