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导入线索表

import_broker_leads

【需要登录】把一整张线索表粘进池子。CSV / TSV / 从 Excel 直接复制的都吃,没有表头也认,认不出的列不丢、全并进备注。按手机号与池内已有的合并(只补空字段,不覆盖手工写过的内容),重导同一张表不会重复建。单次上限 500 条。 【组合链】先把名片 OCR / 聊天记录 / 乱七八糟的 Excel 整理成一张表(这一步才是 agent 的增量)→ import_broker_leads → 把 headerMap 念给用户确认「我是这么理解你这张表的」 → list_broker_leads(q=…) 核对 → scan_broker_matches。 【口径】① 返回只有计数,不给新建线索的列表,要看进了谁请接 list_broker_leads。② skipped 只给行号与去敏预览,整行原文不出参。③ 手机号是归因锚点,没手机号的行将来注册了也算不到你头上。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.6/5.0
Behavior4/5

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

The description richly discloses auth requirements, the 500-row cap, merge-only-empty-fields behavior, no-duplicate re-import, unknown-column handling, and output restrictions. The only gap is that the headerMap confirmation instruction is not fully reconciled with the 'return only counts' statement, leaving minor ambiguity about what the tool actually returns.

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?

The description is dense yet well organized into labeled sections: core behavior, combination workflow, and operational semantics. The main action is front-loaded, and every sentence adds actionable information without filler.

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

Completeness4/5

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

For a batch import tool with no output schema, it covers input format, limits, merge/dedup, return-count semantics, skipped-row handling, and next steps. The remaining gap is the headerMap instruction, which does not clearly state where the mapping comes from or how the agent obtains it.

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 0%, so the description must compensate, and it does: it explains that `text` is the raw pasted table, names accepted formats, notes headerless input, and gives the row limit plus merge/dedup behavior. It never explicitly names the `text` property or clarifies the role of headerMap, so it falls just short of a 5.

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 first sentence names the exact action: paste an entire lead table into the pool. Combined with the name and title, it unambiguously identifies a batch import of broker leads and separates it from single-lead tools like create_broker_lead and verification tools like list_broker_leads.

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 组合链 section provides an explicit when-to-use workflow: normalize upstream data first, then import, confirm headerMap, then verify with list_broker_leads and scan_broker_matches. It also tells the agent when to prefer list_broker_leads instead, making the routing concrete.

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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