nagisanzenin avatar

nagisanzenin

Community

@nagisanzenin

42Followers
|
34Public Repos
|
15Published Skills

Nicotine driven.

Skills Distribution
DomainDeveloper To...Software Engineeri.. (35%)DevOps & Site Reli.. (25%)Security & Quality.. (20%)Product & Document.. (10%)

Agent Skills by nagisanzenin

Showing 15 vetted skills indexed across 3 GitHub repositories.

nagisanzeninnagisanzenin

crucible

Enforce gated scientific pipelines for AI-driven experiments with pre-registration and power analysis.

Community
Advanced
nagisanzeninnagisanzenin
176

security-engineer

Audits application code for OWASP Top 10 vulnerabilities, auth flaws, and data exposure.

Community
Advanced
nagisanzeninnagisanzenin
176

software-engineer

Implements backend services, APIs, and business logic from architecture contracts and specs.

Community
Advanced
nagisanzeninnagisanzenin
176

skill-maker

Creates Claude Code skills and packages them as plugins with GitHub repos and marketplace entries.

Community
Advanced
nagisanzeninnagisanzenin
176

solution-architect

Generates architecture decision records, API contracts, data models, and project scaffolds from scale constraints.

Community
Advanced
nagisanzeninnagisanzenin
176

devops

Generates Dockerfiles, CI/CD pipelines, Terraform modules, and monitoring infrastructure for cloud deployments.

Community
Advanced
nagisanzeninnagisanzenin
176

frontend-engineer

Builds React/Next.js frontends with design systems, typed API clients, and accessibility testing.

Community
Advanced
nagisanzeninnagisanzenin
176

product-manager

Converts product ideas into BRDs with user stories, acceptance criteria, and implementation verification.

Community
Advanced
nagisanzeninnagisanzenin
176

data-scientist

Audits and optimizes LLM usage, experiments, data pipelines, and ML infrastructure with cost modeling.

Community
Advanced
nagisanzeninnagisanzenin
176

qa-engineer

Writes and executes unit, integration, contract, e2e, and performance test suites for services and frontends.

Community
Advanced
nagisanzeninnagisanzenin
171

polymath

Facilitate dialogue and analyze trade-offs for product and technical decisions.

Community
Advanced
nagisanzeninnagisanzenin
176

code-reviewer

Reviews codebases for architecture conformance, code quality, performance, and test coverage gaps.

Community
Advanced
nagisanzeninnagisanzenin
171

production-grade

Orchestrate a multi-agent pipeline for requirements, architecture, development, security, CI/CD, and deployment.

Community
Advanced
nagisanzeninnagisanzenin
176

technical-writer

Generates API references, developer guides, and Docusaurus documentation sites from project artifacts.

Community
Advanced
nagisanzeninnagisanzenin
176

sre

Generates SLOs, chaos experiments, incident runbooks, and capacity plans for production systems.

Community
Advanced

Frequently Asked Questions About nagisanzenin

FAQPage Schema
What tasks can I accomplish with nagisanzenin's skills?▼

You can run the full delivery lifecycle: convert ideas into BRDs and user stories, design architecture with ADRs and API contracts, implement backend services from OpenAPI specs, build React/Next.js frontends, audit for OWASP vulnerabilities, generate test suites, and define SLOs with chaos experiments.

Who should use these skills?▼

Software engineers, solution architects, DevOps and SRE practitioners, QA engineers, security auditors, product managers, and technical writers. The production-grade orchestrator routes requests to the appropriate specialist skill, making it suitable for teams building and operating production systems.

How do the skills run in practice?▼

All specialist skills are marked production-grade internal and are routed via the production-grade orchestrator, which coordinates a multi-stage pipeline covering requirements, architecture, development, security review, CI/CD, and deployment rather than invoking each skill in isolation.

What are the prerequisites and dependencies?▼

Skills operate within the Claude Code skill environment. Inputs include OpenAPI specifications, BRDs, architecture decisions, and existing source code. Outputs include Terraform, Docker, Kubernetes, and GitHub Actions configurations, so familiarity with those platforms is assumed.

Does the data-scientist skill support ML cost optimization?▼

Yes. The data-scientist skill analyzes ML system usage patterns and designs optimization strategies covering model selection, prompt engineering, cost reduction, A/B testing, and experiment design. The crucible skill additionally enforces gated scientific pipelines with pre-registration and power analysis.