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Found 1,266 Skills
Type-driven design principle: transform unstructured data into structured types at system boundaries, making illegal states unrepresentable. Use when writing or reviewing code that validates input, designs data types, defines function signatures, handles errors, or models domain logic. Use when you see validation functions that return void/undefined, redundant null checks, stringly-typed data, boolean flags controlling behavior, or functions that can receive data they shouldn't. Triggers on: "parse don't validate", "type-driven design", "make illegal states unrepresentable", "input validation", "data modeling", "refactor types", "strengthen types", "smart constructor", "newtype", "branded type".
Audit rapidly generated or AI-produced code for structural flaws, fragility, and production risks.
Code file line limit specification: A single code file must have ≤ 300 lines. This is a mandatory restriction with no exceptions.
Use when writing similar code in multiple places. Use when copy-pasting code. Use when making the same change in multiple locations.
Coordinates performance optimization: algorithm, query, and runtime workers in parallel
This skill should be used when the user asks to "set up golangci-lint", "add linting to a Go project", "configure golangci-lint", "fix golangci-lint errors", or needs guidance on Go code quality and linting best practices.
Enforce root-cause fixes over workarounds, hacks, and symptom patches in all software engineering tasks. Use when debugging issues, fixing bugs, resolving test failures, planning solutions, making architectural decisions, or reviewing code changes. Activates gate functions that detect and reject common workaround patterns such as type assertions, lint suppressions, error swallowing, timing hacks, and monkey patches. Don't use for trivial formatting changes or documentation-only edits.
Lead complex software implementation, architecture decisions, and reliable delivery across any modern technology stack. Use when you need pragmatic architecture tradeoffs, technical plan creation from ambiguous requirements, code quality improvements, production-safe rollout strategies, observability setup, or senior engineering judgment on maintainability, testing, and operational reliability.
Run a comprehensive Go-to-Market and launch readiness review for a project phase. Combines marketing content audit, code quality review, performance audit, accessibility audit, infrastructure readiness, and business review with council evaluation. Use before phase launches or when GTM review issues are ready.
Systematic debugging with root cause investigation. Four phases: investigate, analyze, hypothesize, implement. Iron Law: no fixes without root cause. Use when asked to "debug this", "fix this bug", "why is this broken", "investigate this error", or "root cause analysis". Proactively suggest when the user reports errors, unexpected behavior, or is troubleshooting why something stopped working.
Multi-language code quality gate with auto-detection and language-specific linters. Use when user asks to "run quality checks", "quality gate", "lint all", "check everything", "pre-commit checks", or "is this code ready to commit". Use for verifying code quality across polyglot repos. Do NOT use for single-language linting (use code-linting) or comprehensive code review (use systematic-code-review).
Review pull requests for the MiniMax Skills repository. Use when reviewing PRs, validating new skill submissions, or checking existing skills for compliance. Run the validation script first for hard checks, then apply quality guidelines for content review. Triggers: PR review, pull request, validate skill, check skill.