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sync_from_remote

Pull data from remote cloud storage to local for analysis. Specify days to fetch recent N days of data, returning sync results with success, file counts, and errors.

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
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses that the tool pulls data from remote storage, skips dates that already exist locally (implying non-destructive behavior), and returns a structured sync result with success/failure details. It also documents configuration requirements. This is substantial context, though it does not explicitly state that it writes to local storage or that it is a read-only operation on the remote side.

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 well-organized into sections (Args, Returns, Examples, Note). It is longer than necessary for a single-parameter tool, but every section adds value: the note about configuration is critical for successful invocation. The information is front-loaded with the purpose. Some redundancy exists (default days repeated in Args and examples), but overall it is structured and not overly verbose.

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 description covers all essential aspects: purpose, usage scenario, parameter semantics, return format, examples, and configuration prerequisites. The output schema is present, but the description also details the return fields, which is helpful. There is nothing an agent needs to call this tool correctly that is missing.

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 zero description coverage for the 'days' parameter, but the description fully compensates by explaining its meaning ('拉取最近 N 天的数据'), default value (7), allowed values (0, 7, 30), and behavior for each. It even provides examples of usage with different values. This is detailed and precise.

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 states a specific verb and resource: '从远程存储拉取数据到本地' (pull data from remote storage to local). It also explains the use case (crawler stores to cloud storage, MCP server pulls for analysis). This clearly distinguishes it from all sibling tools, which focus on news search, analysis, and configuration, none of which are about synchronization.

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?

The description gives clear context: it is for syncing data from remote storage to local before analysis. It explains the scenario and parameter usage, but does not explicitly mention alternatives or when not to use it. However, since none of the sibling tools are similar, the purpose itself is sufficient guidance for selection.

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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