Skip to main content
Glama

fetch_documentation_page

Retrieve the full Markdown content of a documentation page from a GitHub repository by specifying the repository path and page slug.

Instructions

获取仓库文档的指定页面内容。

根据页面 slug(URL 标识符)获取该页面的完整 Markdown 文档内容。 适用于读取特定章节或页面的详细内容。

返回的 Markdown 页面内容中可能包含两种链接格式:

  1. 仓库文件链接 - 格式: [文件名](文件路径#L开始行号-L结束行号) 例如: [index.ts](index.ts#L1-L28) [package.json](package.json#L1-L77) 这类链接指向仓库内的源代码文件,可提取文件路径和行号范围, 使用 fetch_repository_file(repo_path, file_path, start_line, end_line) 获取具体内容。

  2. 文档导航链接 - 格式: [标题](页面slug) 例如: [概述](1-overview) [快速开始](2-quick-start) 这类链接指向文档的其他页面,使用 fetch_documentation_page(repo_path, 页面slug) 获取该页文档内容。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repo_pathYes仓库路径,格式: owner/repo 或完整 URL
page_slugYes页面 slug,如 "1-overview", "quick-start"
languageNo文档语言,可选 "zh"(中文) 或 "en"(英文)zh
Behavior3/5

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 returned Markdown contains two types of links and explains how to process them, adding behavioral context beyond schema. However, it does not mention any potential limitations, rate limits, or error conditions.

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-structured with bullet points for the link types, making it easy to digest. It is slightly longer than necessary but every sentence adds value, either stating the purpose or explaining how to use the output. No fluff.

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 no output schema, the description effectively explains what the tool returns (Markdown content with link formats) and how to process it with other tools. It covers the main use case comprehensively, though it could mention potential errors or behavior when the page does not exist.

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 coverage is 100%, so the baseline is 3. The description adds no new information about parameters beyond what the schema already provides (e.g., page_slug examples are already in schema description). The description's value lies in usage context, not parameter details.

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 uses a specific verb ('获取') and resource ('仓库文档的指定页面内容'), clearly stating the tool fetches a documentation page by slug. It distinguishes itself from siblings like fetch_repository_file (source code) and search_documentation by explaining link formats and the intended use case.

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 explicitly states it is suitable for reading specific sections/pages, and provides detailed guidance on how to handle the two types of links, including which sibling tool to use for each. It does not explicitly state when not to use this tool, but the context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/ejfkdev/zread-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server