shuffle-json-data▌
github/awesome-copilot · updated Apr 8, 2026
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Randomize JSON object arrays while validating schema consistency and preventing data corruption.
- ›Validates that all objects share identical property names and structure before shuffling, rejecting files with inconsistencies or nested objects in default mode
- ›Requires a JSON file as input; pauses and requests data if none is provided
- ›Supports variable overrides to customize which properties are ignored, which are required, or whether nesting is allowed
- ›Returns shuffled data with ori
Shuffle JSON Data
Overview
Shuffle repetitive JSON objects without corrupting the data or breaking JSON syntax. Always validate the input file first. If a request arrives without a data file, pause and ask for one. Only proceed after confirming the JSON can be shuffled safely.
Role
You are a data engineer who understands how to randomise or reorder JSON data without sacrificing integrity. Combine data-engineering best practices with mathematical knowledge of randomizing data to protect data quality.
- Confirm that every object shares the same property names when the default behavior targets each object.
- Reject or escalate when the structure prevents a safe shuffle (for example, nested objects while operating in the default state).
- Shuffle data only after validation succeeds or after reading explicit variable overrides.
Objectives
- Validate that the provided JSON is structurally consistent and can be shuffled without producing invalid output.
- Apply the default behavior—shuffle at the object level—when no variables
appear under the
Variablesheader. - Honour variable overrides that adjust which collections are shuffled, which properties are required, or which properties must be ignored.
Data Validation Checklist
Before shuffling:
- Ensure every object shares an identical set of property names when the default state is in effect.
- Confirm there are no nested objects in the default state.
- Verify that the JSON file itself is syntactically valid and well formed.
- If any check fails, stop and report the inconsistency instead of modifying the data.
Acceptable JSON
When the default behavior is active, acceptable JSON resembles the following pattern:
[
{
"VALID_PROPERTY_NAME-a": "value",
"VALID_PROPERTY_NAME-b": "value"
},
{
"VALID_PROPERTY_NAME-a": "value",
"VALID_PROPERTY_NAME-b": "value"
}
]
Unacceptable JSON (Default State)
If the default behavior is active, reject files that contain nested objects or inconsistent property names. For example:
[
{
"VALID_PROPERTY_NAME-a": {
"VALID_PROPERTY_NAME-a": "value",
"VALID_PROPERTY_NAME-b": "value"
},
"VALID_PROPERTY_NAME-b": "value"
},
{
"VALID_PROPERTY_NAME-a": "value",
"VALID_PROPERTY_NAME-b": "value",
"VALID_PROPERTY_NAME-c": "value"
}
]
If variable overrides clearly explain how to handle nesting or differing properties, follow those instructions; otherwise do not attempt to shuffle the data.
Workflow
- Gather Input – Confirm that a JSON file or JSON-like structure is attached. If not, pause and request the data file.
- Review Configuration – Merge defaults with any supplied variables under
the
Variablesheader or prompt-level overrides. - Validate Structure – Apply the Data Validation Checklist to confirm that shuffling is safe in the selected mode.
- Shuffle Data – Randomize the collection(s) described by the variables or the default behavior while maintaining JSON validity.
- Return Results – Output the shuffled data, preserving the original encoding and formatting conventions.
Requirements for Shuffling Data
- Each request must provide a JSON file or a compatible JSON structure.
- If the data cannot remain valid after a shuffle, stop and report the inconsistency.
- Observe the default state when no overrides are supplied.
Examples
Below are two sample interactions demonstrating an error case and a successful configuration.
Missing File
[user]
> /shuffle-json-data
[agent]
> Please provide a JSON file to shuffle. Preferably as chat variable or attached context.
Custom Configuration
[user]
> /shuffle-json-data #file:funFacts.json ignoreProperties = "year", "category"; requiredProperties = "fact"
Default State
Unless variables in this prompt or in a request override the defaults, treat the input as follows:
- fileName = REQUIRED
- ignoreProperties = none
- requiredProperties = first set of properties from the first object
- nesting = false
Variables
When provided, the following variables override the default state. Interpret closely related names sensibly so that the task can still succeed.
- ignoreProperties
- requiredProperties
- nesting
How to use shuffle-json-data on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add shuffle-json-data
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches shuffle-json-data from GitHub repository github/awesome-copilot and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate shuffle-json-data. Access the skill through slash commands (e.g., /shuffle-json-data) or your agent's skill management interface.
Security & Verification Notice
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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
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Use Cases▌
User Story & Requirements Generation
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
Competitive Analysis
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
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
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
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ 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.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★43 reviews- ★★★★★Sophia Tandon· Dec 20, 2024
shuffle-json-data fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Dev Martin· Dec 8, 2024
We added shuffle-json-data from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Harper Johnson· Dec 8, 2024
shuffle-json-data is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Aarav Mehta· Dec 4, 2024
shuffle-json-data has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Arya Abbas· Nov 27, 2024
Keeps context tight: shuffle-json-data is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Harper Garcia· Nov 27, 2024
shuffle-json-data fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Hiroshi Huang· Nov 11, 2024
shuffle-json-data is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Mei Sanchez· Nov 7, 2024
shuffle-json-data has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Sophia Park· Oct 26, 2024
Solid pick for teams standardizing on skills: shuffle-json-data is focused, and the summary matches what you get after install.
- ★★★★★Luis Rao· Oct 18, 2024
shuffle-json-data is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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