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rui497

TrendRadar MCP Server

by rui497

sync_from_remote

Pull recent data from remote cloud storage to local for analysis. Use the days parameter to set how many days of data to synchronize, defaulting to 7.

Instructions

从远程存储拉取数据到本地

用于 MCP Server 等场景:爬虫存到远程云存储(如 Cloudflare R2), MCP Server 拉取到本地进行分析查询。

Args: days: 拉取最近 N 天的数据,默认 7 天 - 0: 不拉取 - 7: 拉取最近一周的数据 - 30: 拉取最近一个月的数据

Returns: JSON格式的同步结果,包含: - success: 是否成功 - synced_files: 成功同步的文件数量 - synced_dates: 成功同步的日期列表 - skipped_dates: 跳过的日期(本地已存在) - failed_dates: 失败的日期及错误信息 - message: 操作结果描述

Examples: - sync_from_remote() # 拉取最近7天 - sync_from_remote(days=30) # 拉取最近30天

Note: 需要在 config/config.yaml 中配置远程存储(storage.remote)或设置环境变量: - S3_ENDPOINT_URL: 服务端点 - S3_BUCKET_NAME: 存储桶名称 - S3_ACCESS_KEY_ID: 访问密钥 ID - S3_SECRET_ACCESS_KEY: 访问密钥

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations, the description fully carries the transparency burden. It discloses the sync behavior including skipped local-existing dates, failed dates with errors, and the JSON return structure. It also lists required configuration (config.yaml or environment variables) and environment variable names, providing rich behavioral context.

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 well-structured with sections for Purpose, Args, Returns, Examples, and Note. Every part adds value—parameter semantics, return format, usage examples, and configuration—without redundancy. Length is appropriate given the need to explain the tool's role and requirements.

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?

The tool has one parameter, no output schema in structured data, yet the description thoroughly explains the return fields, parameter options, configuration setup, and usage context. This is complete and exceeds what is typical for tools of similar complexity.

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

Parameters5/5

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

The schema has only 'days' with default 7 and no description (0% coverage). The description compensates by explaining valid values (0, 7, 30), their meanings, and provides examples. This fully clarifies the parameter's semantics.

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 action ('从远程存储拉取数据到本地') with a specific verb (pull) and resource (remote storage to local). It also provides context (MCP Server scenario) and differentiates from siblings by detailing its purpose in the data pipeline.

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

Usage Guidelines4/5

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

It explicitly describes when to use the tool ('用于 MCP Server 等场景:爬虫存到远程云存储...拉取到本地进行分析查询') and specifies configuration prerequisites in the Note section. It does not explicitly mention when not to use it or compare to sibling tools, so a 4 is appropriate.

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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