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独行录 / opcmenu

发起会话

start_conversation
Idempotent

【需要登录】与某位用户开启 1-1 私信会话(已存在则返回原会话,幂等)。可选 productId 标记围绕哪个产品咨询。不能和自己开会话。先用 get_creator / search_people 拿对方 userId。

【返回】conversation(含 id)+ created(这次是不是新建的)+ openerSent(服务端是否已自动替你递了开场语)+ opener/openerKind(你设过自定义开场语就带原文 kind=custom;没设时服务端按对方的产品现生成一句,kind=product/generic,原文不回传,别编)。created=true 且 openerSent=true 时对方已经收到你的开场语了,别再重复问一遍好——接着说正事即可。开场语内容用 get_my_chat_opener 看,改用 set_my_chat_opener。

【每日开场额度】只有新建会话才占额度(回复老会话、别人来找你都不占)。撞上限时返回 429 chat_quota_exhausted,且返回体里直接带出口(额度实况 / 引荐短链与话术 / 积分兑换报价)。那不是临时故障,今天的额度不会自己回来,不要退避重试——照返回里的 exits 跟用户说清楚。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
productIdNo可选,围绕哪个产品的咨询
peerUserIdYes对方用户 id(cuid)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the annotations, it reveals login requirements, server-side automatic opener sending, the created/openerSent semantics, and that opener text is not returned when generated server-side. It also discloses the exact 429 behavior and directs the agent not to treat it as a transient failure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Although the description is long, it is well-organized into labeled sections, and every sentence carries operational weight. The formatting makes dense details like return semantics, quota rules, and related tools easy to scan.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description takes on the responsibility of explaining return values and does so thoroughly: conversation id, created, openerSent, opener/openerKind. It also covers quota errors, the exits payload, and related tools, making it complete for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already fully describes both parameters, so the baseline is 3. The description adds useful context: peerUserId must come from get_creator/search_people, cannot be the agent's own user, and productId marks which product the conversation is about.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific action: starting a 1-1 private conversation with a user, and immediately clarifies idempotency (returns existing conversation) and the optional productId. This clearly distinguishes it from siblings like get_conversation, send_message, and set_my_chat_opener.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly tells the agent to obtain peerUserId via get_creator/search_people, forbids self-conversations, and explains quota consumption only applies to newly created conversations. It also gives a clear when-not-to-retry instruction for the 429 quota-exhausted case.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4.1/5.0
Disambiguation4/5

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.

Naming Consistency4/5

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.

Tool Count1/5

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.

Completeness5/5

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.

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