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guozhiwei01

ai-ssh-mcp

by guozhiwei01

read_logs

Read log files from a remote server, filtering by project, log type (app or nginx), line count, and keyword. Specify the server and optionally narrow results with project, log type, lines, or keyword.

Instructions

读取指定服务器上某个项目的日志文件。

参数:
- server: 服务器中文名,如"生产-API主服务器"
- project: 项目名,如"shop"。服务器只有一个项目时可省略
- log_type: "app"(默认,Laravel log)或 "nginx"(nginx error log)
- lines: 读取最后 N 行,默认 100
- keyword: 关键词过滤,只返回包含该词的行,如"ERROR"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
linesNo
serverYes
keywordNo
projectNo
log_typeNoapp

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

Without annotations, the description carries full burden. It describes the tool as a read operation and explains parameters but does not disclose potential side effects, authentication requirements, or rate limits. The nature of reading logs is low risk so this is adequate.

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 efficient and front-loaded with the purpose. It uses a bullet-style layout. However, it repeats parameter names in the same fashion as the schema, slightly increasing redundancy.

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?

Given the presence of an output schema and the moderate complexity (5 parameters, 1 required), the description covers parameter usage well. It lacks details about output format, but this is partially offset by the output schema.

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?

Schema description coverage is 0%, and the description compensates thoroughly by explaining each parameter with examples and default values. It adds meaning beyond the schema structure, especially for server, project, log_type, and keyword.

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 reads log files from a server and project, specifying the action and resource. It distinguishes from sibling tools like exec_command or list_servers which perform different operations.

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 provides detailed parameter guidance, including defaults and when to omit optional fields. However, it does not explicitly compare with sibling tools or state when not to use this tool, leaving usage context somewhat implied.

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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