Onboarding Compass

    by TopAgent

    1

    Generate role-specific onboarding roadmaps with milestones, resources, and 30-60-90 day plans.

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    Works with the AI tools you already use

    CClaude CodeCCursorCCodex CLIGGitHub CopilotGGemini CLIVVS CodeWWindsurfMManus+14 more

    See it in action

    You say

    I just joined the team. Help me understand this repo and tell me what I should work on first to learn the async queue system.

    Your agent does

    Onboarding: Payment-Processor

    Boot (day 1)

    • [ ] docker-compose up -d
    • [ ] npm test

    Tour (day 2-5)

    1. src/queue/worker.ts - Core consumer logic.

    First PRs

    | # | Task | Where | Teaches | |---|---|---|---| | 1 | Fix retry logger | worker.ts | Async queue flow |

    What you get

    Create a prioritized learning path for new repository contributors.Identify high-impact files and modules for faster codebase navigation.Suggest low-risk first tasks that teach core architectural patterns.Standardize developer onboarding across multiple engineering teams.

    About this skill

    The problem

    New developers waste days context-switching while trying to navigate unfamiliar repositories. Hand-off documentation is often outdated or missing, leaving engineers to guess which modules matter most for their first PR.

    What it does

    • Scans configuration files and entry points to generate immediate bootstrap commands.
    • Identifies the "critical path" modules that handle the majority of application logic.
    • Traces a single feature from entry point to data layer to explain system architecture.
    • Curates a list of low-risk first tasks with specific learning outcomes for each.
    • Decodes project-specific jargon and team conventions into a concise glossary.

    Why this beats prompting it yourself

    Generic prompts result in shallow overviews. This skill actively investigates your unique service topology and git history to prioritize high-traffic files, ensuring the roadmap is based on actual codebase usage rather than just directory structure.

    Use cases

    • Ramping up a new hire on a complex microservice architecture.
    • Taking over a legacy repository with zero active maintainers.
    • Preparing structured hand-off documentation for a departing team member.
    • Onboarding a specialized contractor to a specific slice of the codebase.

    Known limitations

    Focuses on learning paths rather than creating comprehensive API documentation. It does not perform architectural redesigns or code refactoring.

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

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    TopAgent

    13 skills on Agensi

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