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批量建撮合

create_broker_match
Idempotent

【需要登录】一次把用户点头的几对人落库(最多 20 对)。幂等:同一对人不论左右只会有一条,重复调不会建出镜像记录。对方只有站内用户 id、还没收进池的,直接传 bUserId,服务层会先收进池再配。 【组合链】scan_broker_matches → 念给用户 → create_broker_match → get_broker_intro_scripts(含站外,自己发)或 introduce_broker_match(站内拉群)。 【口径】① reason 是「为什么这俩该认识」,四端一字不差地展示给中介自己看,照 scan 给的 reasons 原文写成人话,别写分数。② ⚠ 建撮合会把两条线索都标成 worked=true,那是分账口径的分级字段——别拿建撮合当「试试看」。③ 逐条执行,单条失败不中断整批。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
matchesYes要建的撮合,最多 20 对

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.8/5.0
Behavior5/5

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

The description discloses critical behavioral traits beyond annotations: idempotency (no mirror records on repeat calls), the side effect of marking both leads as worked=true (a billing/revenue field), and the partial-failure behavior (single failure doesn't abort the batch). It also notes the login requirement. These are exactly the kind of behavioral details an agent needs. The annotations (idempotentHint=true, readOnlyHint=false) are consistent with the description.

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

Conciseness4/5

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

The description is dense but well-organized with clear sections (【需要登录】, 【组合链】, 【口径】). Every sentence carries operational weight. It's longer than average, but the complexity of the tool (batch, idempotency, side effects, field semantics) justifies the length. Slight deduction for the dense Chinese formatting that might be harder to parse quickly.

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?

For a batch mutation tool with no output schema, the description covers everything an agent needs: prerequisites (login), batch limits (20), idempotency, side effects, field semantics, error handling, and the surrounding workflow. The sibling list provides additional context for routing. Nothing critical is missing.

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?

Schema coverage is 100%, so the schema already documents all parameters. The description adds value by explaining the bUserId vs bLeadId choice ('对方只有站内用户 id、还没收进池的,直接传 bUserId,服务层会先收进池再配') and by clarifying the reason field's semantics ('别写分数'). It doesn't repeat schema details but adds operational meaning.

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 clearly states the tool's purpose: batch-create broker matches (up to 20 pairs) for pairs the user has approved. It specifies the resource (broker matches), the action (create), and the batch nature. It also distinguishes itself from related tools like introduce_broker_match and get_broker_intro_scripts by showing the workflow chain.

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?

The description provides explicit usage context: it should be used after scan_broker_matches and before get_broker_intro_scripts or introduce_broker_match. It also gives clear guidance on when to use bUserId vs bLeadId, and warns against using it as a 'try it out' action because it marks leads as worked=true. This is strong when-to-use guidance.

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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