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ugf_guide

Returns a usage manual for the FlorrVLM-Agent service, helping newly connected agents learn capabilities, tool list, and recommended call order on first connection.

Instructions

返回本服务的使用手册(给刚接进来的 Agent 看,不用读仓库也能上手)。

用途:第一次连接时先调用它,了解能力边界、工具清单和推荐调用顺序。 入参:section 取 all(默认,全部)/ quick(一屏速览)/ tools(工具清单)/ chains(调用链)/ notes(注意事项与常见坑)。 返回:Markdown 文本手册。工具清单由运行时动态生成,与实际注册的工具始终一致。 下一步:按手册里的调用链开始 perceive_game → predict_all_entities → game_action。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sectionNoall

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.1.0

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations, the description carries the burden. It discloses the return format (Markdown text manual) and a dynamic behavior (tool list generated at runtime, always consistent). It does not mention read-only safety or permission requirements, but for a manual-return tool this is largely implied.

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

Conciseness5/5

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

The description is well-structured with labeled sections (用途, 入参, 返回, 下一步) and front-loaded with the core purpose. Every sentence adds useful information without redundancy.

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

Completeness5/5

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

Given the simple one-parameter tool with an output schema, the description covers everything an agent needs: purpose, when to use, parameter values, return format, and a recommended next step. It is complete and actionable.

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 description coverage is 0% and the schema has no enum, so the description fully compensates by listing all five section values (all, quick, tools, chains, notes) and explaining what each returns. This is exactly the kind of semantic enrichment needed.

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 (返回) and resource (本服务的使用手册), and specifies its audience and scope (for newly connected Agents). It clearly distinguishes itself from all sibling tools as the onboarding guide, and even names itself as the first call in a recommended chain.

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

Usage Guidelines4/5

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

Explicitly says to call it first when first connecting, and provides next steps (perceive_game → predict_all_entities → game_action). It does not state when not to use it, but for a unique guide tool the context is clear enough.

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