vignesh2027/AI-AGENT-SKILLS

accessibility-engineering

Build UIs that work for all users including keyboard navigation, screen readers, and WCAG 2.2

Quellsprache: Englisch

agent-orchestration

Design multi-agent systems with robust tool interfaces, state management, and failure handling

Quellsprache: Englisch

architecture-design

Design systems at the right scale with explicit trade-off documentation

Quellsprache: Englisch

backend-engineering

Design services that are reliable, observable, secure, and maintainable

Quellsprache: Englisch

code-review-and-quality

Conduct staff-engineer-level code reviews across correctness, security, performance, readability, and architecture

Quellsprache: Englisch

code-simplification

Remove accidental complexity without changing behavior — apply Chesterton's Fence

Quellsprache: Englisch

data-pipeline-engineering

Build data pipelines with contracts, lineage, quality gates, and observability

Quellsprache: Englisch

database-design

Schema design, migrations, indexing, and query patterns for maintainable and performant databases

Quellsprache: Englisch

debugging-and-error-recovery

Systematic root-cause analysis — stop guessing, start isolating

Quellsprache: Englisch

deployment-strategy

Deploy with rollback plans, staged rollouts, and feature flags

Quellsprache: Englisch

documentation-and-adrs

Write documentation that stays accurate and decisions that stay recorded

Quellsprache: Englisch

frontend-engineering

Build UIs that are fast, accessible, maintainable, and tested

Quellsprache: Englisch

git-workflow-and-versioning

Branching strategy, commit discipline, PR hygiene, and semantic versioning

Quellsprache: Englisch

idea-refine

Sharpen a vague idea into a buildable, scoped proposal

Quellsprache: Englisch

incident-response

Structured incident response: detect, communicate, mitigate, resolve, and prevent recurrence

Quellsprache: Englisch

infrastructure-as-code

Manage infrastructure with version-controlled, reviewed, and tested IaC

Quellsprache: Englisch

llm-evaluation

Systematically evaluate LLM outputs, prevent regressions, and measure quality

Quellsprache: Englisch

microservices-design

Design service boundaries, contracts, and failure modes for distributed systems

Quellsprache: Englisch

observability-and-monitoring

Design logging, metrics, tracing, and alerting that make systems debuggable in production

Quellsprache: Englisch

performance-optimization

Profile before optimizing; optimize with evidence, not intuition

Quellsprache: Englisch

planning-and-task-breakdown

Decompose work into atomic, independently verifiable tasks

Quellsprache: Englisch

prompt-engineering

Write prompts that are reliable, testable, versioned, and safe

Quellsprache: Englisch

rag-system-design

Design, evaluate, and operate retrieval-augmented generation systems

Quellsprache: Englisch

requirements-analysis

Extract, validate, and document requirements from raw input

Quellsprache: Englisch

risk-assessment

Identify and mitigate technical and delivery risk before it becomes an incident

Quellsprache: Englisch

security-and-hardening

Apply security controls, threat modeling, and hardening to code and infrastructure

Quellsprache: Englisch

source-driven-development

Ground implementation in authoritative sources — specs, RFC, official docs — not assumptions

Quellsprache: Englisch

spec-driven-development

Write a specification before writing any implementation code

Quellsprache: Englisch

test-driven-development

Write tests before implementation to drive design and prove correctness

Quellsprache: Englisch