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sts2-ironclad-agent

by Mentat-Uran
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Python
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    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    B3.3/5.0

    Scored across 9 tools

    Disambiguation4/5

    Most tools have clear, distinct roles across the pipeline: readiness, snapshotting, legal actions, planning, recommendation, execution, stepping, autoplay, and new-run setup. The only mild boundary ambiguity is between execute_proposal and step_once, both of which can submit a single action, but their descriptions distinguish lower-level proposal submission from routed decision execution.

    Naming Consistency3/5

    All names are readable snake_case, but they do not follow a single pattern. get_game_snapshot and get_legal_actions use get_, while plan_map_route, recommend_next_action, and execute_proposal use verb_noun, and preflight, step_once, and autoplay are one-off or compound names.

    Tool Count5/5

    Nine tools is a well-scoped size for an autonomous game agent. Each tool supports a distinct stage of the play loop without excessive redundancy or unnecessary surface area.

    Completeness4/5

    The tool set covers the full gameplay automation loop: preflight checks, state reads, legal-action discovery, path planning, decision recommendation, proposal execution, single-step control, bounded autoplay, and starting a new run. Minor gaps exist around explicit stop/pause or richer configuration control, but the existing tools handle those through local config and autoplay stopping conditions.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources