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    Multi-Agent Team Dispatcher

    1

    Route complex projects to specialist AI agents (architect, dev, UI, QA, PM) with consensus, specs and full-lifecycle automation

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    Multi-Agent Team Dispatcher

    Multi-Agent Team Dispatcher

    Example session with this skill installed

    Coordinate a new feature for my React + FastAPI project: add CSV import with validation, unit tests and a review of the data model. Use the multi-agent team.

    • Read your context and instructions
    • Compiled the multi-agent team dispatcher

    Summary

    The dispatcher routed the task to Architect, Developer, UI Designer and QA agents; the plan passed a two-agent consensus review before implementation.

    StageOwnerOutput
    RequirementsPMstories + acceptance criteria
    DesignArchitectAPI spec, module boundaries
    ImplementationDeveloperCSV parser, endpoint, UI dropzone
    ReviewArchitect2 findings fixed (encoding, chunk size)
    TestingQA14 unit tests, 3 edge-case tests

    Deliverables: code diff, tests (all green), review notes, next steps (add background job for files > 50MB).

    Connects securely to your tools. The creator never sees your data.

    About this skill

    Multi-Agent Team Dispatcher routes your coding tasks to the right specialist AI agent.

    FIVE ROLES

    • Architect: system design, tech-stack decisions, module boundaries
    • Independent Developer: feature implementation, bug fixes
    • UI Designer: interface design, design-system alignment, polish
    • QA Expert: test plans, test cases, acceptance criteria
    • Product Manager: requirement breakdown, task planning, priorities

    EIGHT-STAGE WORKFLOW Requirements -> Design -> Task breakdown -> Implementation -> Code review -> Testing -> Integration check -> Delivery. Each stage produces an artifact the next stage consumes.

    KEY CAPABILITIES

    • Consensus mechanism: multiple agents cross-review plans before code is written
    • Spec-driven development: write docs first, code second, verify against docs last
    • SU (System Understanding): builds an evidence-based understanding of unfamiliar codebases before touching them
    • Autonomous mode: long-running self-directed iteration with guard rails and a safety log
    • Bilingual: full Chinese and English support

    WHO IS IT FOR Solo developers and small teams who want multi-role collaboration (plan review, security review, test coverage) without hiring a team, and anyone migrating or extending an unfamiliar repo.

    Includes a manifest-driven dispatcher, role prompt packs, workflow templates and example projects under MIT License.

    How to use

    Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.

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    Security scanned

    Verified clean 18 days ago

    • Passed all security checks, Safe to install

    Listed18 days ago

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