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Bugly Quality Overview

Community
infometa
bugly-quality-overview

查看 Bugly 产品质量概览(崩溃率、ANR 率、FOOM/OOM 率、启动耗时等)。当用户询问应用的大盘质量、版本质量、今日质量等指标时使用。

Overview

Publisherinfometa
Repositoryworkbuddyskills
Skill namebugly-quality-overview
Stars
376
Forks
124
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by infometa on GitHub. Read the source before you install it.

Installation

Install the Bugly Quality Overview AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/infometa/workbuddyskills/tree/main/connectors/bugly-token/skills
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/infometa/workbuddyskills.git /tmp/workbuddyskills
mkdir -p .claude/skills
cp -r /tmp/workbuddyskills/connectors/bugly-token/skills .claude/skills/bugly-quality-overview
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Bugly Quality Overview in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Bugly Quality Overview on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Bugly Quality Overview is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Bugly 质量概览

本 Skill 配合 Bugly MCP Server(HTTP / streamableHttp,token 模式)使用,提供产品质量概览能力。

能力

  • 查看应用的大盘质量概览(崩溃率 / ANR 率 / FOOM(OOM) 率 / 启动耗时)
  • 查看指定版本的质量概览
  • 查看今天的质量概览

鉴权说明(用户自填 Token 模式)

本连接器使用 auth_mode: "token",凭证由用户自行从 Bugly 平台获取并在 WorkBuddy 表单中填入:

  • BUGLY_ACCESS_TOKEN:访问 Bugly OpenAPI 的个人访问令牌,注入到请求头 Authorization: Bearer ${BUGLY_ACCESS_TOKEN}。
  • BUGLY_API_BASE_URL:MCP Server 入口地址,默认 https://bugly.mcp.it.woa.com,私有部署可改为内网地址。

凭证仅存储在本机 ~/.workbuddy/connectors/bugly-token/ 下,不会上传云端。

如何重新生成 / 更换 Token

如果调用返回未授权(401/403),通常是 Token 失效或被撤销。请到 Bugly 控制台重新生成 Access Token,然后在 WorkBuddy 的连接器设置中重新填入并保存即可,无需重启 WorkBuddy(下次连接即生效)。

Frequently asked questions

What does the Bugly Quality Overview AI skill do?

查看 Bugly 产品质量概览(崩溃率、ANR 率、FOOM/OOM 率、启动耗时等)。当用户询问应用的大盘质量、版本质量、今日质量等指标时使用。

Why use Bugly Quality Overview on TypingMind?

Because you install it once and use it with any model. Bugly Quality Overview is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Bugly Quality Overview in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/infometa/workbuddyskills/tree/main/connectors/bugly-token/skills. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Bugly Quality Overview?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Bugly Quality Overview?

As many as you like. As long as a model supports skills, you can use Bugly Quality Overview with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Bugly Quality Overview AI skill free?

It is published on GitHub by infometa. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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