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iPythoning
by iPythoning

check_version

Checks for updates by comparing local versions of TrendRadar and MCP Server against GitHub remote, returning whether updates are needed. Accepts an optional proxy URL for GitHub access.

Instructions

检查版本更新(同时检查 TrendRadar 和 MCP Server)

比较本地版本与 GitHub 远程版本,判断是否需要更新。

Args: proxy_url: 可选的代理URL,用于访问 GitHub(如 http://127.0.0.1:7890)

Returns: JSON格式的版本检查结果,包含两个组件的版本对比和是否需要更新

Examples: - check_version() - check_version(proxy_url="http://127.0.0.1:7890")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
proxy_urlNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv6.10.0

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains that the tool compares local and GitHub remote versions, checks both TrendRadar and MCP Server, supports an optional proxy for GitHub access, and returns JSON with comparison and update-needed status. This is reasonably transparent, though it does not explicitly state side-effect-free behavior or network failure characteristics.

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 Purpose, Args, Returns, and Examples sections. It is compact, front-loaded with the main purpose, and every section contributes useful information without padding or repetition.

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?

For a simple tool with one optional parameter and an output schema available, the description is complete enough to invoke correctly. It explains the return format, the optional argument, and provides two concrete call examples. Nothing essential is missing for correct usage.

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 input schema has 0% description coverage, so the description must compensate. The Args section fully explains proxy_url as an optional proxy URL to access GitHub, provides a concrete example, and the schema supplies the default null. This adds clear meaning beyond the bare type definition.

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 verb and resource: it checks version updates by comparing local versions with GitHub remote versions, covering both TrendRadar and MCP Server. This makes it immediately distinguishable from sibling tools like sync_from_remote or get_system_status.

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 intended use is implied by the purpose and examples, but the description does not explicitly state when to prefer this tool over alternatives or when not to use it. There is no mention of sibling tools or exclusion cases, so guidance is only inferred.

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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