get_need按 id 查单条需求的完整卡片：类型 / 标题 / 详情 / 配图 / 状态 / 作者（含 canOffer 与代表产品）。登录时附带 isMine 与 displaying。查不到返回 found=false。
【口径】接洽不限人数（没有名额概念），也没有报酬/感谢费。displaying=false 表示作者手动下架了（status 仍是 OPEN——下架只改展示期不改状态），别再向用户推荐它。
【相关 resource】opcmenu://need/{id} 【后续】想接这条需求 → contact_need（需登录），它返回 conversationId 可以直接接 send_message。
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | 需求 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?
Beyond the readOnlyHint/idempotentHint annotations, the description discloses auth-dependent fields (isMine, displaying), not-found behavior (found=false), the semantics of displaying=false (manual delist, status stays OPEN), and the no-quota/no-reward business rule.
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 main purpose is front-loaded, and the additional domain rules, resource link, and follow-up route are separated into labeled sections. Every sentence adds operational value; there is no filler.
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?
With no output schema, the description carries the burden of explaining return content, conditional fields, missing-record behavior, and critical display/status semantics. It also tells the agent what to do next, making it complete for a single getter.
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 only parameter id is already described as '需求 id（cuid）'. The description references '按 id' and the resource link but adds no substantive parameter details beyond the schema, so the baseline 3 applies.
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 first line states a specific verb and resource: '按 id 查单条需求的完整卡片' and enumerates the returned fields. It clearly distinguishes this single-id detail getter from list/search/recommendation siblings.
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?
It gives clear context: use for a single need card by id, and explains not to recommend needs with displaying=false. It also routes to contact_need for taking the need, but does not explicitly contrast with sibling query tools like search_needs or list_needs_feed.
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.