关注主理人
follow_creator【需要登录】关注某位主理人(用户 id)。互相关注即成为好友,对方设为「好友可见」的链接会对你可见。幂等:重复关注 no-op。先用 list_creators / get_creator 拿 id。
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| userId | Yes | 目标用户 id(cuid) |
follow_creator【需要登录】关注某位主理人(用户 id)。互相关注即成为好友,对方设为「好友可见」的链接会对你可见。幂等:重复关注 no-op。先用 list_creators / get_creator 拿 id。
| Name | Required | Description | Default |
|---|---|---|---|
| userId | Yes | 目标用户 id(cuid) |
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?
描述在注解之外补充了关键行为:需要登录、互相关注成为好友、好友可见链接的可见性变化、以及幂等重复关注无效果。这些副作用和前置条件不是注解能直接推导出来的,对代理正确评估调用后果非常有价值。
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?
描述仅四句话,每句话都有明确用途:登录要求、动作对象、副作用、幂等性、参数获取方式。信息密度高且前置了最重要的登录限制,无冗余内容。
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?
对于单参数、无输出 schema 的简单关注操作,描述已覆盖登录条件、参数来源、幂等性、好友关系效果和可见性变化。注解也补充了 idempotentHint 和 destructiveHint,整体信息完整,没有明显缺失。
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?
输入 schema 对 userId 的描述已覆盖 100%,基线为 3。描述额外说明“先用 list_creators / get_creator 拿 id”,为代理提供了获取该参数的实用路径,这超出了 schema 本身的信息,因此加一分。
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?
描述明确说明具体动作是“关注某位主理人(用户 id)”,并进一步解释互相关注会成为好友、好友可见链接会对你可见。这清楚地将 follow_creator 与 follow_product、unfollow_creator 等同类工具区分开,动词和对象都具体无歧义。
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?
描述给出了明确的使用上下文:需要登录后才能关注,并建议先用 list_creators / get_creator 获取目标用户 id。虽然没有逐一说明何时不应使用本工具,但已提供足够的前置条件和操作路径,AI 能据此正确触发或引导用户。
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.