给主理人写口碑
endorse_creator【需要登录】给某位主理人写一段推荐口碑(无星级,文字必填 ≥4 字,可选关系 relation)。不能给自己 / 未认领占位号写;互相拉黑时不可写。一人对一人一条,再次调用即编辑。
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| body | Yes | 推荐口碑文字(必填,≥4 字) | |
| userId | Yes | 主理人用户 id | |
| relation | No | 你与 TA 的关系,如 合作过/用户/同行,可选 |
endorse_creator【需要登录】给某位主理人写一段推荐口碑(无星级,文字必填 ≥4 字,可选关系 relation)。不能给自己 / 未认领占位号写;互相拉黑时不可写。一人对一人一条,再次调用即编辑。
| Name | Required | Description | Default |
|---|---|---|---|
| body | Yes | 推荐口碑文字(必填,≥4 字) | |
| userId | Yes | 主理人用户 id | |
| relation | No | 你与 TA 的关系,如 合作过/用户/同行,可选 |
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 annotations (readOnlyHint=false, idempotentHint=true), the description discloses login requirements, the one-record-per-pair constraint, and the important upsert behavior that calling again edits the existing endorsement. It also adds business rules around self-endorsement, unclaimed accounts, and mutual blocks that annotations cannot express.
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?
A single dense sentence front-loads the login requirement, then states the operation, parameter essentials, target exclusions, and create-or-edit behavior. No filler or redundant restatement of the tool name exists.
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 three-parameter tool with no output schema, the definition covers auth, required/optional fields, invalid target cases, and edit-on-recall semantics. With schema covering parameter formats and annotations covering read-only/destructive flags, nothing essential for correct invocation is missing.
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%, so the baseline is 3. The description adds value beyond the schema by constraining userId semantics: the target cannot be the caller, cannot be an unclaimed placeholder, and the operation is blocked under mutual block. It also clarifies the relation parameter is optional and body is required text, though the schema already encodes body minLength and relation optionality.
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: writing a recommendation testimonial for a specific 主理人. It also distinguishes from siblings by noting '无星级' (no star rating), separating it from rate_product, and by describing the create-or-edit behavior that get_creator_endorsements would not cover.
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 when-to-use context and explicit when-not constraints: cannot write for yourself, cannot write for an unclaimed placeholder, and cannot write when mutually blocked. However, it does not name alternative tools or explicitly route the agent to a read-only sibling for viewing endorsements, so it stops short of full 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.