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sshwsfc
by sshwsfc

get_table_records

Query data table records by applying filters, sorting, pagination, and field projection.

Instructions

查询数据表的记录列表,支持过滤、排序、分页和字段投影

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tableNameYes表名称(不是ID)
filterNo查询过滤条件,类似于关系库的where参数。第一级的key可以是字段名称或者or等特殊参数。 - 字段名称支持完全匹配和模糊搜索 - or表示多个条件中满足其中一个即可 - 示例1(完全匹配): {"status": "online", "type": "sensor"} - 示例2(模糊搜索): {"name": {"$regex": "设备", "$options": "i"}} - 示例3(or条件): {"$or": [{"status": "online"}, {"type": "sensor"}]} - 示例4(组合查询): {"status": "online", "$or": [{"type": "sensor"}, {"type": "controller"}]}
sortNo排序条件,类似于关系库的order by参数。格式{key:value},key是需要排序的字段名称,value是1和-1,1表示升序,-1表示降序。 - 可以同时按照多个字段排序,排序优先级按照字段顺序 - 示例1(单字段升序): {"createTime": 1} - 示例2(单字段降序): {"createTime": -1} - 示例3(多字段排序): {"status": 1, "createTime": -1} (先按status升序,相同值按createTime降序)
limitNo分页查询参数,指定返回的记录数量限制,格式{key:value},key是limit,value是实际值。类似于关系库的LIMIT语句。
skipNo分页查询参数,指定跳过的记录数量,用于分页,格式{key:value},key是skip,value是实际值。类似于关系库的OFFSET语句。
projectNo字段投影,指定需要查询返回的字段,格式{key:value},key是字段名称,value是1表示包含该字段。 - 示例: {"name": 1, "status": 1, "createTime": 1} 只返回name、status和createTime字段
withCountNo总条数统计参数,格式{key:value},key是固定值withCount,value是true。会在响应头加上count字段,对应值为总条数。 - 示例: {"withCount": true}
Behavior2/5

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

With no annotations provided, the description carries the full burden for behavioral disclosure. It only mentions supported features but does not reveal traits like read-only nature, rate limits, or what happens with large result sets.

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 a single sentence that covers all main features without redundancy. It is concise, though slightly more structure could improve readability.

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

Completeness3/5

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

No output schema exists, and the description does not explain the return value format. While parameters are well-documented, the lack of output details and behavioral context leaves the description incomplete for an AI agent.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already thoroughly documents each parameter. The description provides no additional meaning beyond the schema, meriting a baseline score of 3.

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 queries a record list from a data table, supporting filtering, sorting, pagination, and projection. It distinguishes itself from sibling tools like get_record_by_id (single record) and get_table_by_id (table metadata).

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

Usage Guidelines3/5

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

The description implies usage for listing records but does not explicitly state when to use this tool versus alternatives. It lacks guidance on when not to use it (e.g., for a single record) or prerequisites.

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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