Agent Skills Hub

ci

Automated CI/CD incident response, failure analysis, and remediation for GitHub Actions pipelines. Resolves build and test failures with safety guardrails.

releasing-software

A pre-flight release checklist system to verify build paths, tests, and CI status before tagging, preventing failed deployments and repetitive retagging cycles.

autoresearch

Autonomous multi-team codebase improvement agent with specialized modes: narrow (goal-directed), broad (hypothesis-divergent), and sweep (quality-focused).

skill-repo

Standardize, validate, and manage Netresearch AI agent skill repositories with automated structure enforcement, distribution workflows, and licensing compliance tools.

contract-testing

Implement consumer-driven contract testing for microservices using Pact, schema validation, and API versioning to prevent breaking changes and ensure distributed team coordination.

github-release-management

Intelligent GitHub release orchestration using AI swarms for automated versioning, multi-platform deployment, testing, and rollback management.

cicd-pipeline-qe-orchestrator

Orchestrate end-to-end quality engineering across CI/CD pipelines, from commit-stage unit testing and shift-left strategies to production-stage synthetic monitoring and compliance gates.

pr-review-fix-loop

Orchestrate an automated PR review-fix loop. Dispatches subagents to analyze code, CI status, and comments, then applies iterative fixes until the PR reaches a passing state.

devops

Manage CI/CD workflows, Docker containerization, and infrastructure configurations for the multi-chain crypto wallet system.

land

Automated PR lifecycle management: monitors conflicts, resolves CI failures, handles review feedback, and executes squash-merges for safe code integration.

xp-practices

Implement Extreme Programming (XP) practices including TDD, pair programming, and continuous integration to enhance team collaboration and technical excellence in software engineering.

shift-left-testing

Accelerate software delivery by shifting testing to the earliest development phases, using AI-driven requirements validation, TDD, and automated CI pipelines to reduce defect costs.