agency-agents vs Kerno: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of agency-agents and Kerno — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
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agency-agents
msitarzewski
Open-source collection of specialized AI agent personalities installable into Claude Code, Cursor, Codex and more.
Key features
- Specialized Agent Roster: Role-specific agents with deep domain expertise rather than generic prompt templates.
- Personality-Driven Design: Each agent has its own voice, communication style and approach.
- Deliverable Focus: Agents define real code, processes and measurable outcomes.
- Desktop Installer App: A native app for macOS, Linux and Windows installs agents with a click and auto-updates.
- Multi-Tool Support: Works with Claude Code, Cursor, Codex, Gemini CLI, OpenCode, Qwen, Windsurf and others.
- Selective Installation: Install only the divisions or teams you need.
Best for
- A developer installs a frontend specialist agent into Claude Code for UI work.
- A founder assembles a virtual agency of marketing and product agents.
- A team uses agent files as reference for writing its own agent prompts.
- A user installs the same roster across Cursor and Codex with the desktop app.
- A community manager adapts a community-focused agent for social outreach.
- A contributor submits a new specialized agent through a pull request.
Kerno
Kerno
Autonomously writes, runs, and maintains integration tests in your IDE to cover backend codebases and speed safe shipping.
Key features
- Autonomous Test Generation: Automatically writes integration tests by analyzing backend code paths and service interactions to produce tests that exercise edge cases and typical workflows.
- In-IDE Execution: Runs generated integration tests directly from the developer's IDE, providing immediate feedback and fast iteration without leaving the development environment.
- Test Maintenance and Updating: Detects code changes and intelligently updates or repairs existing integration tests to prevent test rot and reduce manual upkeep.
- Comprehensive Coverage Mapping: Identifies untested areas of the backend and generates tests to fill gaps, helping teams achieve broader and deeper integration coverage.
- CI/CD Integration: Designed to integrate with existing continuous integration pipelines so generated tests can be executed automatically as part of builds and deployments.
- Regression Detection: Continuously runs and compares integration test outcomes to detect regressions early and surface actionable failure context to developers.
- Autonomous generation of integration tests that cover backend code paths
- Execution of integration tests from within the developer IDE
- Automated maintenance and updates of tests as code evolves
- Agent runtime for executing workflows and tests
- Support materials and example repositories in multiple languages (Go, Java/Kotlin, Python, TypeScript)
- Benchmarking methodology (Kerno MCP) for agent workflow evaluation with logs and review
- Integrates with developer workflows and CI/CD pipelines
- Provides developer challenges and code samples for onboarding and evaluation
Best for
- Accelerating backend feature delivery by auto-generating integration tests that validate new endpoints and service interactions before merge.
- Reducing regressions by continuously maintaining and running integration tests that adapt as the codebase changes.
- Onboarding new team members by providing a ready suite of integration tests that demonstrate expected system behavior and interactions.
- Improving test coverage for legacy services by automatically creating integration tests that exercise rarely used or complex code paths.
- Integrating automated integration tests into CI pipelines to block unsafe deployments and ensure consistent safety checks across releases.
- Automatically generate and run integration tests for microservices and backend APIs
- Keep integration tests up to date after refactors or API changes
- Run and debug integration tests directly from the IDE during development
- Integrate test execution into CI/CD pipelines to increase release confidence
- Benchmark agent-driven workflows and collect logs for human and structural review
- Provide coding challenges and test harnesses for technical hiring and candidate evaluation