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Agent Skill · 研究检索

earllm-build(早期构建)

earllm-build 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

earllm-build 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 56,324。

总安装 456周安装 19GitHub Stars 35,673下载 152核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:earllm-build(早期构建)
来源仓库:https://github.com/sickn33/antigravity-awesome-skills
仓库路径:skills/earllm-build
安装命令:
npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill earllm-build
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill earllm-build

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于 EarLLM One Android 项目的开发与维护。连接蓝牙耳机的语音管道与 LLM 推理服务。支持 SCO 麦克风整理与 Kotlin/Compose UI 开发。需关注蓝牙音频协议与移动端资源管理。

适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。earllm-build 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/earllm-build

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill ear…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

earllm-build 怎么安装?

在终端执行 npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill earllm-build。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

earllm-build 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

earllm-build 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill earllm-build 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

earllm-build 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

earllm-build 用的人多吗?

公开数据是累计安装 456 次,近一周安装 19 次,下载 152 次,GitHub 35,673 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

earllm-build 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 来源仓库有 35,673 星,维护活跃度相对可查。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
earllm-build

早期构建 · 本页

45635,673执行命令未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

EarLLM One — Build & Maintain

Overview

Build, maintain, and extend the EarLLM One Android project — a Kotlin/Compose app that connects Bluetooth earbuds to an LLM via voice pipeline.

When to Use This Skill

  • When the user mentions "earllm" or related topics
  • When the user mentions "earbudllm" or related topics
  • When the user mentions "earbud app" or related topics
  • When the user mentions "voice pipeline kotlin" or related topics
  • When the user mentions "bluetooth audio android" or related topics
  • When the user mentions "sco microphone" or related topics

Do Not Use This Skill When

  • The task is unrelated to earllm build
  • A simpler, more specific tool can handle the request
  • The user needs general-purpose assistance without domain expertise

How It Works

EarLLM One is a multi-module Android app (Kotlin + Jetpack Compose) that captures voice from Bluetooth earbuds, transcribes it, sends it to an LLM, and speaks the response back.

Project Location

C:\Users\renat\earbudllm

Module Dependency Graph

app ──→ voice ──→ audio ──→ core-logging
  │       │
  ├──→ bluetooth ──→ core-logging
  └──→ llm ──→ core-logging

Modules And Key Files

ModulePurposeKey Files
core-loggingStructured logging, performance trackingEarLogger.kt, PerformanceTracker.kt
bluetoothBT discovery, pairing, A2DP/HFP profilesBluetoothController.kt, BluetoothState.kt, BluetoothPermissions.kt
audioAudio routing (SCO/BLE), capture, headset buttonsAudioRouteController.kt, VoiceCaptureController.kt, HeadsetButtonController.kt
voiceSTT (SpeechRecognizer + Vosk stub), TTS, pipelineSpeechToTextController.kt, TextToSpeechController.kt, VoicePipeline.kt
llmLLM interface, stub, OpenAI-compatible clientLlmClient.kt, StubLlmClient.kt, RealLlmClient.kt, SecureTokenStore.kt
appUI, ViewModel, Service, Settings, all screensMainViewModel.kt, EarLlmForegroundService.kt, 6 Compose screens

Build Configuration

  • SDK: minSdk 26, targetSdk 34, compileSdk 34
  • Build tools: AGP 8.2.2, Kotlin 1.9.22, Gradle 8.5
  • Compose BOM: 2024.02.00
  • Key deps: OkHttp, AndroidX Security (EncryptedSharedPreferences), DataStore, Media

Target Hardware

DeviceModelKey Details
PhoneSamsung Galaxy S24 UltraAndroid 14, One UI 6.1, Snapdragon 8 Gen 3
EarbudsXiaomi Redmi Buds 6 ProBT 5.3, A2DP/HFP/AVRCP, ANC, LDAC

Critical Technical Facts

These are verified facts from official documentation and device testing. Treat them as ground truth when making decisions:

  1. Bluetooth SCO is limited to 8kHz mono input on most devices. Some support 16kHz mSBC. BLE Audio (Android 12+, TYPE_BLE_HEADSET = 26) supports up to 32kHz stereo. Always prefer BLE Audio when available.
  2. startBluetoothSco() is deprecated since Android 12 (API 31). Use AudioManager.setCommunicationDevice(AudioDeviceInfo) and clearCommunicationDevice() instead. The project already implements both paths in AudioRouteController.kt.
  3. Samsung One UI 7/8 has a known HFP corruption bug where A2DP playback corrupts the SCO link. The app handles this with silence detection and automatic fallback to the phone's built-in mic.
  4. Redmi Buds 6 Pro tap controls must be set to "Default" (Play/Pause) in the Xiaomi Earbuds companion app. If set to ANC or custom functions, events are handled internally by the earbuds and never reach Android.
  5. Android 14+ requires FOREGROUND_SERVICE_MICROPHONE permission and foregroundServiceType="microphone" in the service declaration. RECORD_AUDIO must be granted before startForeground().
  6. VOICE_COMMUNICATION audio source enables AEC (Acoustic Echo Cancellation), which is critical to prevent TTS audio output from feeding back into the STT microphone input. Never change this source without understanding the echo implications.
  7. Never play TTS (A2DP) while simultaneously recording via SCO. The correct sequence is: stop playback → switch to HFP → record → switch to A2DP → play response.

Data Flow

Headset button tap
  → MediaSession (HeadsetButtonController)
  → TapAction.RECORD_TOGGLE
  → VoicePipeline.toggleRecording()
  → VoiceCaptureController captures PCM (16kHz mono)
  → stopRecording() returns ByteArray
  → SpeechToTextController.transcribe(pcmData)
  → LlmClient.chat(messages)
  → TextToSpeechController.speak(response)
  → Audio output via A2DP to earbuds

Adding A New Feature

  1. Identify which module(s) are affected
  2. Read existing code in those modules first
  3. Follow the StateFlow pattern — expose state via MutableStateFlow / StateFlow
  4. Update MainViewModel.kt if the feature needs UI integration
  5. Add unit tests in the module's src/test/ directory
  6. Update docs if the feature changes behavior

Modifying Audio Capture

  • VoiceCaptureController.kt handles PCM recording at 16kHz mono
  • WAV headers use hex byte values (not char literals) to avoid shell quoting issues
  • VU meter: RMS calculation → dB conversion → normalized 0-1 range
  • Buffer size: getMinBufferSize().coerceAtLeast(4096)

Changing Bluetooth Behavior

  • BluetoothController.kt manages discovery, pairing, profile proxies
  • Earbuds detection uses name heuristics: "buds", "earbuds", "tws", "pods", "ear"
  • Always handle both Bluetooth Classic and BLE Audio paths

Modifying The Llm Integration

  • LlmClient.kt defines the interface — keep it generic
  • StubLlmClient.kt for offline testing (500ms simulated delay)
  • RealLlmClient.kt uses OkHttp to call OpenAI-compatible APIs
  • API keys stored in SecureTokenStore.kt (EncryptedSharedPreferences)

Generating A Build Artifact

After code changes, regenerate the ZIP:

## From Project Root

powershell -Command "Remove-Item 'EarLLM_One_v1.0.zip' -Force -ErrorAction SilentlyContinue; Compress-Archive -Path (Get-ChildItem -Exclude '*.zip','_zip_verify','.git') -DestinationPath 'EarLLM_One_v1.0.zip' -Force"

Running Tests

./gradlew test --stacktrace          # Unit tests
./gradlew connectedAndroidTest       # Instrumented tests (device required)

Phase 2 Roadmap

  • Real-time streaming voice conversation with LLM through earbuds
  • Smart assistant: categorize speech into meetings, shopping lists, memos, emails
  • Vosk offline STT integration (currently stubbed)
  • Wake-word detection to avoid keeping SCO open continuously
  • Streaming TTS (Android built-in TTS does NOT support streaming)

Stt Engine Reference

EngineSizeWERStreamingBest For
Vosk small-en40 MB~10%YesReal-time mobile
Vosk lgraph128 MB~8%YesBetter accuracy
Whisper tiny40 MB~10-12%No (batch)Post-utterance polish
Android SpeechRecognizer0 MBvariesYesOnline, no extra deps

Best Practices

  • Provide clear, specific context about your project and requirements
  • Review all suggestions before applying them to production code
  • Combine with other complementary skills for comprehensive analysis

Common Pitfalls

  • Using this skill for tasks outside its domain expertise
  • Applying recommendations without understanding your specific context
  • Not providing enough project context for accurate analysis

平台分布

Codex

38.19%
按下载量换算58

Claude

30.1%
按下载量换算46

Cursor

19.42%
按下载量换算30

Gemini CLI

9.68%
按下载量换算15

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill earllm-build 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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