查一人公司主页
get_company按 slug 获取某个一人公司主页(公开视角:仅返回已发布 PUBLISHED 的公司;本人 owner 可见自己任意状态的公司)。查不到返回 found=false。
【何时用】用户想看某家一人公司在做什么。
【相关 resource】opcmenu://company/{slug}
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | 公司主页 slug(URL 上 /c/<slug>) |
get_company按 slug 获取某个一人公司主页(公开视角:仅返回已发布 PUBLISHED 的公司;本人 owner 可见自己任意状态的公司)。查不到返回 found=false。
【何时用】用户想看某家一人公司在做什么。
【相关 resource】opcmenu://company/{slug}
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | 公司主页 slug(URL 上 /c/<slug>) |
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?
Annotations already signal read-only and idempotent behavior, and the description adds meaningful context beyond that: only PUBLISHED companies are returned for the public, owners can see their own non-published companies, and a not-found result returns found=false. This gives the agent a clear behavioral contract even without an output schema.
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?
The description is compact and well-structured: core function first, then when-to-use guidance, then a resource link. Each section earns its place and adds distinct value without redundancy.
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?
For a single-parameter read tool, the description covers the lookup mechanism, visibility rules, owner exception, and not-found behavior. With no output schema, the found=false note helps fill the return-value gap. Nothing critical is missing for correct invocation.
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?
Schema coverage is 100%, and the slug parameter already has a description ('公司主页 slug(URL 上 /c/<slug>)'). The tool description adds no new parameter semantics beyond restating that lookup is by slug, so the baseline score of 3 is appropriate.
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?
The description states a specific verb and resource ('按 slug 获取某个一人公司主页') and clarifies the public/owner visibility distinction. It differentiates itself from sibling tools like get_my_company and list_companies by scoping to a single company by slug with PUBLISHED-only behavior.
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?
The '【何时用】' section gives clear context: use it when the user wants to see what a specific one-person company does. It does not explicitly name alternatives or exclusion cases, but the visibility rules ('仅返回已发布 PUBLISHED 的公司;本人 owner 可见自己任意状态的公司') imply when it applies and when it might not.
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.