get_collaboration_goal【需要登录】看独行录目标详情、我的权限、合作人、任务。服务校验成员权限；includeClosed=true 包含已了结任务，最多 200 条，reachingLimit 表示可能截断。读任务会幂等补周期期次。创建任务用 create_collaboration_task，发起人改目标用 update_collaboration_goal。
| Name | Required | Description | Default |
|---|---|---|---|
| goalId | Yes | ||
| includeClosed | No |
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 annotations, the description discloses authentication needs, server-side permission checks, the closed-task filtering behavior, the 200-row cap, the reachingLimit truncation signal, and the idempotent backfill of periodic iterations on read. This adds substantial behavioral context without contradicting the annotations.
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 information-dense. Every sentence contributes a distinct fact: purpose, login/permission, filtering and limits, idempotent side effect, and routing to sibling tools. There is no filler or 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?
Even without an output schema, the description enumerates what is returned (goal details, permissions, collaborators, tasks), covers auth and permission checks, explains edge-case behavior (truncation, closed tasks, backfill), and points to sibling tools for related mutations. This is sufficiently complete for an agent to invoke it correctly.
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 description coverage is 0%, so the description must carry weight. It provides strong semantics for includeClosed (closed tasks, max 200, reachingLimit truncation), but goalId is only implied as the target goal, not explicitly documented. Since goalId is the sole required parameter, this is a partial gap.
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 clearly states the tool views goal details, permissions, collaborators, and tasks ('看独行录目标详情、我的权限、合作人、任务'). It uses a specific verb and resource, and the mention of create_collaboration_task and update_collaboration_goal helps distinguish it from mutation 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 explicitly states the login and member-permission requirement, explains includeClosed=true behavior and the 200-item limit, and routes the agent to create_collaboration_task for creating tasks and update_collaboration_goal for initiator edits. This gives clear when-to-use and when-to-use-alternative guidance.
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.