读我的兴趣偏好
get_my_preferences【需要登录】返回当前用户设置的兴趣标签(用于回显,改前先读)。
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
get_my_preferences【需要登录】返回当前用户设置的兴趣标签(用于回显,改前先读)。
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
注解已提供 readOnlyHint=true、idempotentHint=true、destructiveHint=false 的完整安全画像,描述在此基础上补充了“需要登录”的认证前提——这是注解未覆盖且对调用成败至关重要的信息。描述与注解无矛盾,且增加了场景说明。
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
单句描述包含三项关键信息:登录要求、返回值、调用时机,且认证这一前置条件被前置标注。没有冗余文字,每部分都承载独立信息。
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
对零参数、注解丰富的简单读取工具而言,描述已覆盖认证前提、返回内容和调用时机,基本完备。缺少返回格式的具体说明,也未显式写出写对应工具名,但由于无输出 schema 且工具极简,影响很小。
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
工具无参数,按规则基准为 4。描述中的“当前用户”补充了身份解析语义——即工具基于登录会话确定目标对象,而非接受用户 ID 参数,这对代理理解调用方式有实际价值。
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
描述使用具体动词“返回”和明确资源“当前用户设置的兴趣标签”,清楚说明了工具的功能与范围,并点明数据用途是“回显”。这与众多 get_my_* 兄弟工具(如 get_my_profile、get_my_card)能自然区分开。
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
“用于回显,改前先读”明确给出了使用时机:在修改偏好之前先读取当前值用于界面回显。虽然没有直接点名 set_my_preferences 这个写操作兄弟工具,但“改前先读”已隐含了读写配对的调用顺序,上下文清晰。
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly documented purpose, often with explicit 'when to use' guidance and cross-references, making the vast majority easy to tell apart. A few clusters (get_my_brief, get_my_positioning, get_my_work, get_my_dispatch) and data-overlapping get_my_card vs get_my_profile require careful reading, but descriptions are detailed enough to prevent serious misselection.
The overwhelming majority follow snake_case verb_noun conventions (create_product, update_need, list_my_signups). Minor deviations include noun-only feed names (personalized_feed, random_feed), inconsistency between 'prefs' and 'preferences' in notification tools, and a mix of update_* and set_* for mutations, but the pattern remains predictable overall.
137 tools is an extreme mismatch for any MCP server, far exceeding the 50+ threshold for a score of 1. Even with a broad multi-domain platform, this volume makes tool selection and navigation impractical and heavily burdens the agent's context window.
The surface covers full lifecycles for needs, products, activities/signups, conversations, collaboration goals/tasks, dispatch, profile/onboarding, and supporting resources like companies, parks, policies, and ratings. Deliberate omissions (no user-post creation, no organizer profile editing via agent) are explicitly documented, so core workflows have no obvious dead ends.