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Glama

qr_login_start

Starts Bilibili QR login, returning QR code and qrcode_key. Poll qrcode_key until user confirms to complete login.

Instructions

开始扫码登录:返回二维码(图片内容 + PNG 路径 + ASCII 文本 + 原始链接)。

把二维码展示给用户,用 B 站 App 扫码并在手机上点确认; 然后用返回的 qrcode_key 调 qr_login_poll 轮询状态,confirmed 即登录成功 (保存的 cookies.json 会被后续需要登录的工具自动使用)。 render: "png"=返回图片内容与 PNG 路径(默认,推荐); "ascii"=仅返回终端文本二维码;"none"=仅返回链接。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
renderNopng

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.8/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does well: it discloses that this is a login-start operation, that it produces a cookie file for later tools, and that user confirmation is required. It could add more about whether repeated calls invalidate previous QR sessions, but the disclosed behavior is already substantial.

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 compact, front-loaded with the return payload, and then explains the usage flow and parameter options. Every sentence adds operational value without redundancy.

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 one-parameter tool with no output schema and no annotations, the description is complete: it explains what the tool returns, how to proceed, what side effects occur, and all render option meanings. An agent has enough context to call it correctly and continue the login flow.

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 only defines a 'render' string with 0% description coverage, but the description fully explains the three accepted values: 'png' returns image content and PNG path (default, recommended), 'ascii' returns terminal text QR code, and 'none' returns only the link. This is exactly the semantic value the schema lacks.

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 names a specific verb and resource: '开始扫码登录' (start QR-code login) and explicitly lists what it returns (image content, PNG path, ASCII text, raw link). It is clearly distinguishable from the sibling qr_login_poll, which is the polling step.

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

Usage Guidelines5/5

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

The description gives an explicit workflow: display QR to user, scan with Bilibili app, confirm on phone, then call qr_login_poll with the returned qrcode_key. It also states that saved cookies will be used automatically by later tools, which tells the agent when and why to invoke this tool.

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