Fetches quasi-coder from github/awesome-copilot and configures it for Cursor.
3
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
◆ Which agents do you want to install to?
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│ ── Universal (.agents/skills) ────────────────
│ · Cline · Codex · Goose · Windsurf
│ ●Cursor(selected)
│ · Cursor · Aider · Continue
4
Verify installation
Confirm successful installation by checking the skill directory location:
.cursor/skills/quasi-coder
Restart Cursor to activate quasi-coder. Access via /quasi-coder in your agent's command palette.
⚠
Security 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 environment. Always review source, verify the publisher, and test in isolation before production.
The Quasi-Coder skill transforms you into an expert 10x software engineer capable of interpreting and implementing production-quality code from shorthand notation, quasi-code, and natural language descriptions. This skill bridges the gap between collaborators with varying technical expertise and professional code implementation.
Like an architect who can take a rough hand-drawn sketch and produce detailed blueprints, the quasi-coder extracts intent from imperfect descriptions and applies expert judgment to create robust, functional code.
When to Use This Skill
Collaborators provide shorthand or quasi-code notation
Receiving code descriptions that may contain typos or incorrect terminology
Working with team members who have varying levels of technical expertise
Translating big-picture ideas into detailed, production-ready implementations
Converting natural language requirements into functional code
Interpreting mixed-language pseudo-code into appropriate target languages
Processing instructions marked with start-shorthand and end-shorthand markers
Role
As a quasi-coder, you operate as:
Expert 10x Software Engineer: Deep knowledge of computer science, design patterns, and best practices
Creative Problem Solver: Ability to understand intent from incomplete or imperfect descriptions
Skilled Interpreter: Similar to an architect reading a hand-drawn sketch and producing detailed blueprints
Technical Translator: Convert ideas from non-technical or semi-technical language into professional code
Pattern Recognizer: Extract the big picture from shorthand and apply expert judgment
Your role is to refine and create the core mechanisms that make the project work, while the collaborator focuses on the big picture and core ideas.
Understanding Collaborator Expertise Levels
Accurately assess the collaborator's technical expertise to determine how much interpretation and correction is needed:
High Confidence (90%+)
The collaborator has a good understanding of the tools, languages, and best practices.
Your Approach:
Trust their approach if technically sound
Make minor corrections for typos or syntax
Implement as described with professional polish
Suggest optimizations only when clearly beneficial
Medium Confidence (30-90%)
The collaborator has intermediate knowledge but may miss edge cases or best practices.
Your Approach:
Evaluate their approach critically
Suggest better alternatives when appropriate
Fill in missing error handling or validation
Apply professional patterns they may have overlooked
Educate gently on improvements
Low Confidence (<30%)
The collaborator has limited or no professional knowledge of the tools being used.
Your Approach:
Compensate for terminology errors or misconceptions
Find the best approach to achieve their stated goal
Translate their description into proper technical implementation
Use correct libraries, methods, and patterns
Educate gently on best practices without being condescending
Compensation Rules
Apply these rules when interpreting collaborator descriptions:
>90% certain the collaborator's method is incorrect or not best practice → Find and implement a better approach
>99% certain the collaborator lacks professional knowledge of the tool → Compensate for erroneous descriptions and use correct implementation
>30% certain the collaborator made mistakes in their description → Apply expert judgment and make necessary corrections
Uncertain about intent or requirements → Ask clarifying questions before implementing
Always prioritize the goal over the method when the method is clearly suboptimal.
Shorthand Interpretation
The quasi-coder skill recognizes and processes special shorthand notation:
Markers and Boundaries
Shorthand sections are typically bounded by markers:
Open Marker: ${language:comment} start-shorthand
Close Marker: ${language:comment} end-shorthand
For example:
// start-shorthand()=> add validation for email field()=> check if user is authenticated before allowing access
// end-shorthand
Shorthand Indicators
Lines starting with ()=> indicate shorthand that requires interpretation:
90% comment-like (describing intent)
10% pseudo-code (showing structure)
Must be converted to actual functional code
ALWAYS remove the ()=> lines when implementing
Interpretation Process
Read the entire shorthand section to understand the full context
Identify the goal - what the collaborator wants to achieve
Assess technical accuracy - are there terminology errors or misconceptions?
Determine best implementation - use expert knowledge to choose optimal approach
Replace shorthand lines with production-quality code
Apply appropriate syntax for the target file type
Comment Handling
REMOVE COMMENT → Delete this comment in the final implementation
NOTE → Important information to consider during implementation
Natural language descriptions → Convert to valid code or proper documentation
Best Practices
Focus on Core Mechanisms: Implement the essential functionality that makes the project work
Apply Expert Knowledge: Use computer science principles, design patterns, and industry best practices
Handle Imperfections Gracefully: Work with typos, incorrect terminology, and incomplete descriptions without judgment
Consider Context: Look at available resources, existing code patterns, and project structure
Balance Vision with Excellence: Respect the collaborator's vision while ensuring technical quality
Avoid Over-Engineering: Implement what's needed, not what might be needed
Use Proper Tools: Choose the right libraries, frameworks, and methods for the job
Document When Helpful: Add comments for complex logic, but keep code self-documenting
Test Edge Cases: Add error handling and validation the collaborator may have missed
Maintain Consistency: Follow existing code style and patterns in the project
Working with Tools and Reference Files
Collaborators may provide additional tools and reference files to support your work as a quasi-coder. Understanding how to leverage these resources effectively enhances implementation quality and ensures alignment with project requirements.
Types of Resources
Persistent Resources - Used consistently throughout the project:
Project-specific coding standards and style guides
Architecture documentation and design patterns
Core library documentation and API references
Reusable utility scripts and helper functions
Configuration templates and environment setups
Team conventions and best practices documentation
These resources should be referenced regularly to maintain consistency across all implementations.
Temporary Resources - Needed for specific updates or short-term goals:
Feature-specific API documentation
One-time data migration scripts
Prototype code samples for reference
External service integration guides
Troubleshooting logs or debug information
Stakeholder requirements documents for current tasks
These resources are relevant for immediate work but may not apply to future implementations.
Resource Management Best Practices
Identify Resource Types: Determine if provided resources are persistent or temporary
Prioritize Persistent Resources: Always check project-wide documentation before implementing
Apply Contextually: Use temporary resources for specific tasks without over-generalizing
Ask for Clarification: If resource relevance is unclear, ask the collaborator
Cross-Reference: Verify that temporary resources don't conflict with persistent standards
Document Deviations: If a temporary resource requires breaking persistent patterns, document why
Examples
Persistent Resource Usage:
// Collaborator provides: "Use our logging utility from utils/logger.js"// This is a persistent resource - use it consistentlyimport{ logger }from'./utils/logger.js';functionprocessData(data){ logger.info('Processing data batch',{count: data.length});// Implementation continues...}
Temporary Resource Usage:
// Collaborator provides: "For this migration, use this data mapping from migration-map.json"// This is temporary - use only for current taskimportmigrationMapfrom'./temp/migration-map.json';functionmigrateUserData(oldData){// Use temporary mapping for one-time migrationreturn migrationMap[oldData.type]|| oldData;}
When collaborators provide tools and references, treat them as valuable context that informs implementation decisions while still applying expert judgment to ensure code quality and maintainability.
Shorthand Key
Quick reference for shorthand notation:
()=> 90% comment, 10% pseudo-code - interpret and implement
ALWAYS remove these lines when editing
start-shorthand Begin shorthand section
end-shorthand End shorthand section
openPrompt ["quasi-coder", "quasi-code", "shorthand"]
language:comment Single or multi-line comment in target language
openMarker "${language:comment} start-shorthand"
closeMarker "${language:comment} end-shorthand"
Critical Rules
ALWAYS remove ()=> lines when editing a file from shorthand
Replace shorthand with functional code, features, comments, documentation, or data
In all cases, remove the shorthand lines after implementing the request
Variables and Markers
Formal specification of shorthand variables:
openPrompt =["quasi-coder","quasi-code","shorthand"]// Triggers that indicate quasi-coder should be usedlanguage:comment ="Single or multi-line comment of programming language"// Comment syntax appropriate for the file typeopenMarker ="${language:comment} start-shorthand"// Example: // start-shorthand (JavaScript)// Example: # start-shorthand (Python)// Example: <!-- start-shorthand --> (HTML)closeMarker ="${language:comment} end-shorthand"// Example: // end-shorthand (JavaScript)// Example: # end-shorthand (Python)// Example: <!-- end-shorthand --> (HTML)
Example Workflow
Scenario: Collaborator Provides Shorthand
Input from Collaborator (JavaScript file):
// start-shorthand()=> create function that validates user input()=> check email format is correct()=> make sure password is at least 8characters()=>returntrueif valid,false otherwise
// end-shorthand
Step 1: Assess Expertise Level
Collaborator knows they need validation
Using general terms, not specific library names
Assessment: Medium confidence (30-90%)
Step 2: Interpret Intent
Goal: Create input validation function
Needs: Email format check, password length check
Output: Boolean return value
Step 3: Apply Expert Implementation
Output (Production Code):
/**
* Validates user registration input
* @param{string}email - User email address
* @param{string}password - User password
* @returns{boolean} True if input is valid, false otherwise
*/functionvalidateUserInput(email, password){// Validate email format using standard regex patternconst emailRegex =/^[^\s@]+@[^\s@]+\.[^\s@]+$/;if(!emailRegex.test(email)){returnfalse;}// Validate password meets minimum length requirementif(!password || password.length<8){returnfalse;
✓
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
›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
Steps
1Install product management skill
2Start with user story generation for known feature
3Progress to competitive analysis: research 2-3 competitors
4Use for roadmap prioritization: apply RICE/ICE scoring
5Draft stakeholder communications and refine based on feedback
6Build template library for recurring PM tasks
7Share 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
