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Glama

game_action

Executes florr.io gameplay actions (move, attack, defend, synthesize, idle) to apply agent decisions as real or dry-run inputs.

Instructions

执行一个游戏动作。

用途:把决策落地成实际操作。 入参:action_type 必填,取 move / attack / defend / synthesize / idle; move 时必须给 x、y 目标坐标(内部会做拟人化路径微扰和偶发停顿)。 切换套装请用 switch_set,不要用本工具。 返回:动作执行结果文本。默认 dry-run(UGF_DRY_RUN=1)只校验参数并返回描述, 不会真的动键鼠;只有在获得授权的环境里才关闭 dry-run。 下一步:回到 perceive_game → predict_all_entities 的循环;遇到 AFK 弹窗用 handle_afk。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
xNo
yNo
action_typeYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.1.0

TDQS

A4.8/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, so the description carries the full burden, and it delivers: it discloses the dry-run default (UGF_DRY_RUN=1) that only validates parameters, that real input control requires an authorized environment, and that move actions apply anthropomorphic path perturbation and occasional pauses. These are unique behavioral traits not available elsewhere.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with purpose, then structured as 用途 / 入参 / 返回 / 下一步. Every sentence adds value, though the repeated formatting labels are slightly verbose; it remains compact for the amount of information conveyed.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations and 0% schema coverage, the description is nearly complete: purpose, parameters, return format, and workflow context are all present. It could be improved by listing the return fields or error cases, but it already provides a full picture for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must compensate. It does: action_type is said to be required with allowed values 'move / attack / defend / synthesize / idle', and x/y are described as target coordinates required when action_type is move. This fully covers the parameter semantics that the bare schema omits.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('执行一个游戏动作') and clarifies the intent: turning a decision into an actual operation. It explicitly distinguishes itself from the sibling switch_set ('切换套装请用 switch_set,不要用本工具').

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit when-to-use in the workflow loop ('回到 perceive_game → predict_all_entities 的循环'), names a direct alternative (switch_set), and describes a specific escalation path ('遇到 AFK 弹窗用 handle_afk'). It even states the dry-run condition under which the tool is appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.