列我的产品
get_my_products【需要登录】列出当前用户名下的产品(含待认领 / 已发布 / 已下架等全部状态,以及每个产品的全部链接)。
【何时用】agent 要改某个产品的链接/资料前先列出来拿 productId;或盘点「我发布了哪些东西」。
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
get_my_products【需要登录】列出当前用户名下的产品(含待认领 / 已发布 / 已下架等全部状态,以及每个产品的全部链接)。
【何时用】agent 要改某个产品的链接/资料前先列出来拿 productId;或盘点「我发布了哪些东西」。
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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?
The description discloses a login requirement ('需要登录') and clarifies that the result includes all product statuses and all links, adding behavioral context beyond the readOnly/idempotent annotations. It does not detail pagination or exact response shape, but that is a minor gap for a simple read-only list tool.
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, with the core function stated first, followed by output scope and practical usage guidance. Every sentence adds value and there is no redundancy or 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?
For a zero-parameter read-only listing tool, the description covers the login requirement, the exact scope of results, and the intended use case of obtaining productId. Even without an output schema, an agent has enough information to select and invoke the tool 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?
The tool has zero parameters and an empty input schema, so there are no parameter semantics for the description to clarify. The baseline of 4 for zero-parameter tools applies here.
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 a specific action and resource: '列出当前用户名下的产品' (list the current user's products). It also specifies the output scope — all statuses and all links — which distinguishes it from sibling tools like list_products or search_products.
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 concrete use cases: getting a productId before modifying a product's links/profile, or taking inventory of published items. It provides clear context for when to use the tool, though it does not explicitly say when not to use it or name alternatives.
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.