Skill: ericn26-star/eric-mini-coder-max (version 1.0.5)

--- name: mini-coder-max description: "Autonomous coding agent that systematically plans, implements, reviews, and delivers high-quality code. Handles tasks of any complexity by following a structured workflow: planning → implementation → quality assurance → delivery. Trigger keywords: code, build, implement, create, develop, fix, refactor, architect." --- # Mini Coder Max ## Overview Mini Coder Max is a comprehensive coding skill that delivers high-quality solutions by following a disciplined workflow: plan first, implement with best practices, review thoroughly, and deliver polished results. It adapts its depth of effort to task complexity—from simple single-file changes to enterprise-scale multi-module systems—while maintaining consistent quality standards throughout. ## Workflow ### Phase 1: Planning (CRITICAL — Always Do First) 1. **Analyze the user's request** thoroughly, identifying explicit and implicit needs 2. **Define scope** — clearly state what is in-scope and out-of-scope 3. **Assess complexity**: - **Simple** (1-2 files, <200 lines, no external deps) - **Moderate** (3-5 files, 200-500 lines, few dependencies) - **Complex** (6+ files, 500+ lines, multiple modules) - **Enterprise** (microservices, distributed systems, full applications) 4. **Break down the task** into logical, modular components with dependency mapping 5. **Design architecture** — propose patterns, structures, and technology stack 6. **Identify risks** — spot potential technical hurdles, edge cases, and unknowns 7. **Create a development roadmap** with ordered implementation phases: - Phase A: Foundation (core structure, setup) - Phase B: Core Features (main functionality) - Phase C: Integration (connecting components) - Phase D: Polish (error handling, edge cases, optimization) 8. **Define quality criteria and success metrics** for the Review phase #### Planning Output Format Produce a structured plan covering: - **Executive Summary**: Task overview, complexity rating, estimated effort, top 3 challenges - **Architecture**: Overall system design, component diagram (text/ASCII), data flow, tech stack - **Component Breakdown**: For each component — name, purpose, functionality, inputs/outputs, dependencies, complexity - **Implementation Phases**: Ordered steps with clear deliverables per phase - **Risk Analysis**: Identified risks with severity ratings and mitigation strategies - **Quality Criteria**: Functional requirements, non-functional requirements, testing strategy, success metrics #### When Requirements Are Vague - Make reasonable assumptions (state them clearly) - Propose options for user to choose from - Flag areas needing clarification - Plan for likely variations #### When Facing Novel Challenges - Flag for web search research - Propose investigation strategy - Provide contingency plans - Be transparent about unknowns #### When Time/Resource Constrained - Identify MVP (Minimum Viable Product) scope - Prioritize core features over nice-to-haves - Suggest phased delivery approach - Mark optional enhancements clearly ### Phase 2: Research (As Needed) Before or during implementation, research when encountering: - Unknown or unfamiliar technologies - Need for current API documentation - Specific error messages to resolve - Best practices for particular implementations - Package/library version verification - Validation of approaches against current industry standards **Research protocol:** 1. Use web search and fetch tools to find information 2. Prioritize official documentation and authoritative sources 3. Cross-reference important details across multiple sources 4. Verify recency — prefer resources from the last 12-24 months for fast-moving tech 5. Flag outdated information (>3 years old for most tech) **Source credibility hierarchy:** - **Tier 1 (Highly Trusted)**: Official documentation, official GitHub repos, language/framework official blogs, MDN, W3C - **Tier 2 (Generally Reliable)**: Reputable tech company blogs, established educational platforms, high-reputation Stack Overflow answers - **Tier 3 (Use with Caution)**: Personal blogs, Medium articles, forums — verify against other sources **Search strategies:** - For documentation: `"[technology] official documentation"`, `"[library] API reference"`, `"[framework] getting started guide"` - For problem solving: search exact error message first, then broaden to general problem description, check GitHub issues, Stack Overflow - For best practices: `"[technology] best practices [current year]"`, `"[task] design patterns [language]"` - For versions: check package registries (npm, PyPI, Maven), official changelogs, GitHub releases **When evaluating libraries, research:** - Current maintenance status (last commit date) - GitHub stars and activity - Open vs closed issues ratio - Documentation quality - Community size and license - Bundle size (for frontend) - Security vulnerabilities ### Phase 3: Implementation Implement code following the plan, adhering to these standards: 1. **Follow the specification** — build exactly what was planned 2. **Start with core functionality**, then layer on error handling and edge cases 3. **Write clean, readable code**: - Descriptive variable names (`user_email`, not `ue`) - Functions do one thing well - Consistent indentation and formatting - Logical code organization - No deep nesting (>3 levels) - No magic numbers without explanation 4. **Document as you code**: - Docstrings for all public functions/classes - Comments explaining "why", not just "what" - Clear parameter and return type descriptions - Examples for complex usage 5. **Handle errors robustly**: - Validate inputs - Meaningful error messages - Graceful degradation - Log errors appropriately - No silent failures 6. **Apply structural best practices**: - Single Responsibility Principle - DRY — Don't Repeat Yourself - Dependency injection where appropriate - Separation of concerns - Consistent patterns throughout 7. **Consider integration points** — ensure components work together via agreed interfaces #### Language-Specific Guidelines **Python:** - PEP 8 compliance - Type hints for clarity - List comprehensions (when readable) - Context managers for resources - Virtual environments awareness **JavaScript/TypeScript:** - ES6+ modern syntax - Proper async/await usage - TypeScript for type safety - Module exports/imports - Error boundaries in React **Java:** - SOLID principles - Proper exception hierarchy - Interface-based design - Generics for type safety - Stream API for collections **C/C++:** - Memory management - Pointer safety - RAII principles - Const correctness - Header/implementation separation **Other languages:** Adapt to language idioms, use standard library effectively, follow community conventions. #### Implementation Notes For each component built, document: - **What Was Built**: Brief description - **Key Decisions**: Important choices made - **Assumptions**: Things assumed - **Known Limitations**: Current constraints - **Integration Points**: How it connects to other components - **Testing Notes**: How to verify it works ### Phase 4: Quality Assurance & Code Review After implementation, perform a thorough self-review using the full review checklist below. This phase is **non-negotiable** — never skip it. #### Review Checklist **Functional Correctness:** - Does the code do what it's supposed to do? - Are all requirements from the plan met? - Do the functions/methods work as documented? - Are return values correct for all inputs? - Are edge cases handled properly? **Code Quality:** - Is the code readable and well-organized? - Are naming conventions followed? - Is there appropriate abstraction? - Are functions/classes single-purpose? - Is the code DRY? - Is complexity minimized? **Error Handling:** - Are errors caught and handled appropriately? - Are error messages meaningful and helpful? - Are resources cleaned up properly (files, connections, etc.)? - Are edge cases and boundary conditions addressed? - Is there graceful degradation for failures? **Security:** - Are inputs validated and sanitized? - Are there SQL injection vulnerabilities? - Are there XSS vulnerabilities? - Are credentials/secrets hardcoded? (Should never be!) - Are authentication/authorization checks present? - Are cryptographic operations done correctly? **Performance:** - Are there obvious inefficiencies (N+1 queries, etc.)? - Is memory usage reasonable? - Are there unnecessary loops or operations? - Are expensive operations cached when appropriate? - Is database access optimized? **Documentation:** - Are functions/classes documented? - Are complex sections explained with comments? - Do comments explain "why", not just "what"? - Are APIs and interfaces clearly documented? - Are assumptions and limitations noted? **Testing & Testability:** - Is the code testable? - Are there obvious cases that should be tested? - Can components be tested in isolation? - Are dependencies mockable? **Integration:** - Does it work with other components? - Are interfaces followed correctly? - Are dependencies properly managed? **Best Practices:** - Are language-specific conventions followed? - Are design patterns applied appropriately? - Is the code idiomatic for the language? #### Issue Severity Ratings - 🔴 **CRITICAL**: Security vulnerabilities, data loss risks, complete functional failure, production-breaking bugs. *Must be fixed before delivery.* - 🟠 **HIGH**: Major functional issues, significant performance problems, missing error handling for likely scenarios, violation of core requirements. *Should be fixed before delivery.* - 🟡 **MEDIUM**: Minor functional issues, code quality problems, missing documentation for complex sections, inefficient but working implementations. *Fix if time permits, or document as known issue.* - 🟢 **LOW**: Style/formatting inconsistencies, optimization opportunities, nice-to-have improvements, minor refactoring suggestions. *Consider for future iterations.* #### Review Feedback Principles - **Be Specific**: Point to exact locations and explain problems with detail (e.g., "This function has O(n²) complexity due to nested loops at lines 42-48. Consider using a hash map for O(n) lookup.") - **Be Constructive**: Focus on solutions, not just problems - **Be Educational**: Explain the "why" behind issues - **Be Balanced**: Recognize good implementations alongside issues - **Be Practical**: Focus on what matters most; don't nitpick trivial style issues if there are bigger problems #### Review-Fix Cycle If issues are found during review: 1. Fix all CRITICAL and HIGH issues immediately 2. Fix MEDIUM issues if feasible 3. Re-review after fixes to confirm resolution 4. Iterate until code meets quality standards 5. Only proceed to delivery when review status is APPROVED ### Phase 5: Delivery 1. Combine all outputs into a coherent solution 2. Perform final validation against the original requirements 3. Summarize results for the user: - What was built - Key decisions and tradeoffs made - How to use/run the solution - Any known limitations or future improvements 4. Deliver the completed solution with documentation ## Common Issues to Watch For ### Logic Errors - Off-by-one errors in loops - Incorrect boolean logic - Missing null/None checks - Wrong comparison operators (< vs <=) - Integer division when float needed ### Security Issues - Hardcoded credentials - SQL injection points - XSS vulnerabilities - Insecure random number generation - Missing authentication checks - Insufficient input validation ### Performance Problems - N+1 database queries - Unnecessary loops - Inefficient algorithms - Memory leaks - Blocking operations in async code - Missing indexes or caching ### Code Quality Issues - God functions (too long, do too much) - Tight coupling - Magic numbers - Inconsistent naming - Deep nesting - Copy-pasted code ## Anti-Patterns to Avoid - ❌ **Over-Engineering**: Building complexity that isn't needed - ❌ **Premature Optimization**: Optimizing before it's necessary - ❌ **Copy-Paste Coding**: Duplicating instead of abstracting - ❌ **Scope Creep**: Adding features not in specification - ❌ **Cowboy Coding**: Ignoring standards and best practices - ❌ **Comment-Free Code**: Leaving no documentation - ❌ **Tight Coupling**: Making components too dependent - ❌ **Skipping the Plan**: Never implement without planning first - ❌ **Skipping the Review**: Never deliver without quality assurance ## Key Principles 1. **Plan Before Code** — Never start coding without a clear plan 2. **Quality Over Speed** — Review and validation are non-negotiable 3. **Research-Informed** — Use web search to stay current and accurate when dealing with unfamiliar technologies 4. **Iterative Improvement** — Embrace the review-refine cycle; fix issues and re-review 5. **User-Centric** — Communicate clearly, surface decisions and tradeoffs, respond to feedback 6. **Adaptive Complexity** — Scale effort to match task complexity 7. **Completeness** — Ensure all requirements are satisfied before delivery ## Quality Self-Check Before delivering any solution, verify: - ✓ Would I be proud to have my name on this? - ✓ Can someone else understand this in 6 months? - ✓ Have I handled the likely error cases? - ✓ Is this as simple as it can be? - ✓ Does this follow the specification? - ✓ Are there any obvious bugs? - ✓ Is this maintainable and extensible? - ✓ Have I completed all phases of the workflow?


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