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Claude Skills by DevelopersGlobal
github.com/DevelopersGlobal31 skills0 installs26 views
- Ai Output ValidationValidates, parses, and sanitizes AI-generated outputs before they reach end users or downstream systems. Structured output enforcement, schema validation, and fallback handling.Votes: 0GitHub stars: 65
- Api DesignDesign stable, versioned, self-documenting APIs. Easy to use correctly, hard to use incorrectly. Apply Hyrum's Law from day one.Votes: 0GitHub stars: 65
- Ci Cd PipelinesAutomated quality gates from commit to production. Every merge to main is potentially shippable. No manual steps in the deployment path.Votes: 0GitHub stars: 65
- Code ExplanationGet layered, context-aware explanations of unfamiliar code. Understand what it does, why it was written that way, and how to work with it safely.Votes: 0GitHub stars: 65
- Code ReviewStructured code review focusing on correctness, security, and maintainability. Correctness before style. Every reviewer comment must be actionable.Votes: 0GitHub stars: 65
- Context LoadingLoad minimum necessary context into agent context windows. Prevents token bloat, reduces cost, and improves focus. Only load what the current task needs.Votes: 0GitHub stars: 65
- Debugging MethodologySystematic root cause analysis for production and development bugs. Hypothesis-driven debugging — never guess-and-check.Votes: 0GitHub stars: 65
- DocumentationDocument decisions, not just implementations. ADRs for architectural choices, inline docs for non-obvious code, and runbooks for operational knowledge.Votes: 0GitHub stars: 65
- Error HandlingGraceful degradation and meaningful error messages. Errors are first-class citizens, not afterthoughts. Every error path is designed, not discovered.Votes: 0GitHub stars: 65
- Frontend EngineeringAccessible, performant, responsive UI patterns. Component design, state management discipline, and Core Web Vitals compliance.Votes: 0GitHub stars: 65
- Git WorkflowTrunk-based development with atomic commits, clean history, and meaningful commit messages. Every commit should be deployable.Votes: 0GitHub stars: 65
- Goal Driven ExecutionTransforms imperative instructions into declarative goals with verifiable success criteria. Enables autonomous looping until verified completion.Votes: 0GitHub stars: 65
- Hallucination PreventionDetects and mitigates LLM hallucinations in production pipelines. Validates AI-generated facts, code, and decisions before they reach end users or downstream systems.Votes: 0GitHub stars: 65
- Idea To SpecConverts vague ideas into concrete, testable specifications with acceptance criteria. No implementation begins without a spec.Votes: 0GitHub stars: 65
- Incremental CodingBuild in verifiable increments. Never implement more than can be tested right now. Ship partial working systems over complete broken ones.Votes: 0GitHub stars: 65
- Integration TestingTest real system boundaries, not mocks of mocks. Integration tests verify that components work together, not that they work in isolation.Votes: 0GitHub stars: 65
- Meeting Notes To TasksConverts unstructured meeting notes into structured, assigned, time-bounded action items. Never leave a meeting without knowing who does what by when.Votes: 0GitHub stars: 65
- Multi Agent OrchestrationDesigns and coordinates multi-agent pipelines where specialized agents collaborate to complete complex tasks. Includes communication protocols, failure handling, and state management.Votes: 0GitHub stars: 65
- ObservabilityStructured logging, distributed tracing, and alerting for AI systems and traditional services. You can't fix what you can't see.Votes: 0GitHub stars: 65
- Performance OptimizationMeasure first, optimize second. Data-driven performance improvements with before/after benchmarks and production validation.Votes: 0GitHub stars: 65
- Production DeploymentZero-downtime deployments with pre-flight checks, staged rollouts, and rollback plans. Never ship to production without a verified rollback strategy.Votes: 0GitHub stars: 65
- Prompt Injection DefenseGuards AI agents and LLM-powered applications against prompt injection attacks — both direct and indirect. Validates AI inputs and outputs at every trust boundary.Votes: 0GitHub stars: 65
- Rag And MemoryPatterns for Retrieval-Augmented Generation (RAG) and agent memory systems. Retrieves only relevant context, prevents context bloat, and maintains coherent state across sessions.Votes: 0GitHub stars: 65
- RefactoringSafe, behavior-preserving code transformation backed by tests. Refactor with evidence, not instinct.Votes: 0GitHub stars: 65
- Research And SummarizeDistill complex topics into layered, actionable summaries. Start with the key insight, layer in detail, end with recommended next action.Votes: 0GitHub stars: 65
- Security HardeningApplies OWASP Top 10, secrets management, and least-privilege principles before any code ships. Security is a build step, not an afterthought.Votes: 0GitHub stars: 65
- Simplicity FirstPrevents overengineering by enforcing minimum viable code. No speculative features, no premature abstractions, no unnecessary complexity.Votes: 0GitHub stars: 65
- Surgical ChangesEnforces minimal code modifications — touch only what you must. Prevents drive-by refactoring, comment deletions, and style changes unrelated to the task.Votes: 0GitHub stars: 65
- Task DecompositionBreaks features into atomic, independently verifiable tasks. No task should take more than 4 hours. Unblocks parallel work and reduces integration risk.Votes: 0GitHub stars: 65
- Test Driven DevelopmentRed-green-refactor cycle with meaningful coverage. Tests are written before implementation. Coverage is a side effect of good tests, not the goal.Votes: 0GitHub stars: 65
- Think Before CodingForces explicit reasoning before writing any code. Surfaces assumptions, manages confusion, and prevents hallucination by demanding clarity upfront.Votes: 0GitHub stars: 65