Token导航 LogoToken导航

Agent Skill · 研究检索

full-stack-bootstrap(全栈引导程序)

full-stack-bootstrap 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。

full-stack-bootstrap 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,权限为接触敏感数据;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 73,674 个 Skill 里排第 37,977。

总安装 1,639周安装 69GitHub Stars 38下载 574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:full-stack-bootstrap(全栈引导程序)
来源仓库:https://github.com/terrylica/cc-skills
仓库路径:skills/full-stack-bootstrap
安装命令:
npx skills add https://github.com/terrylica/cc-skills --skill full-stack-bootstrap
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/terrylica/cc-skills --skill full-stack-bootstrap

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。

full-stack-bootstrap 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。适用于需要根据关键词或任务场景进行信息筛选的场景。通过安装命令从指定仓库添加技能,可结合原始 README 核验用法。

安装前建议确认权限范围和维护状态,避免触发不必要的数据访问。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。

来源仓库内路径:skills/full-stack-bootstrap

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/terrylica/cc-skills --skill full-stack-bootstr…;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

    它需要接触敏感数据,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

full-stack-bootstrap 怎么安装?

在终端执行 npx skills add https://github.com/terrylica/cc-skills --skill full-stack-bootstrap。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

full-stack-bootstrap 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。

full-stack-bootstrap 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

full-stack-bootstrap 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。

full-stack-bootstrap 用的人多吗?

公开数据是累计安装 1,639 次,近一周安装 69 次,下载 574 次,GitHub 38 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。

full-stack-bootstrap 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。

先想清楚的地方

  • 需要接触敏感数据,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

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 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
full-stack-bootstrap

全栈引导程序 · 本页

1,63938接触敏感数据未明确通过

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

Full Stack Bootstrap

One-time bootstrap of the entire TTS + Telegram bot stack: Kokoro TTS engine (MLX-Audio on Apple Silicon), Telegram bot via BotFather, secrets management, environment configuration, and shell symlinks.

Platform: macOS (Apple Silicon)
Self-Evolving Skill: This skill improves through use. If instructions are wrong, parameters drifted, or a workaround was needed — fix this file immediately, don't defer. Only update for real, reproducible issues.

When to Use This Skill

  • First-time setup of the tts-tg-sync plugin
  • Reinstalling after a clean OS install or hardware migration
  • Setting up a new machine with the full TTS + Telegram stack
  • Recovering from a broken installation (run kokoro-install.sh --uninstall first)

Requirements

ComponentRequiredInstallation
BunYesbrew install oven-sh/bun/bun
miseYesbrew install mise
uvYesbrew install uv
Python 3.13Yesuv python install 3.13
HomebrewYesAlready installed on macOS dev machines
Apple Silicon (M1+)YesRequired for MLX Metal acceleration

Workflow Phases

Phase 0: Preflight Check

Verify all prerequisites are installed and accessible:

command -v bun    # Bun runtime for TypeScript bot
command -v mise   # Environment manager
command -v uv     # Python package manager
uv python list | grep 3.13  # Python 3.13 available

If any tool is missing, install via Homebrew (brew install <tool>). Python 3.13 is installed via uv python install 3.13.

Phase 1: Kokoro TTS Engine Install

Run the bundled installer script:

bash scripts/kokoro-install.sh --install

This performs:

  1. Requires Apple Silicon (fails fast on Intel/Linux)
  2. Creates venv at ~/.local/share/kokoro/.venv with Python 3.13 via uv
  3. Installs PyPI deps (mlx-audio, soundfile, numpy)
  4. Copies kokoro_common.py and tts_generate.py from plugin bundle to ~/.local/share/kokoro/
  5. Downloads Kokoro-82M-bf16 MLX model from HuggingFace (mlx-community/Kokoro-82M-bf16)
  6. Writes version.json with mlx_audio version, backend, and model ID

Phase 2: BotFather Token Setup

Guide the user through Telegram BotFather to create a bot token:

  1. Open Telegram, search for @BotFather
  2. Send /newbot, follow prompts (name + username)
  3. Copy the HTTP API token
  4. Verify token: curl -s "https://api.telegram.org/bot<TOKEN>/getMe" | jq.ok
  5. Get chat_id by sending a message to the bot, then: curl -s "https://api.telegram.org/bot<TOKEN>/getUpdates" | jq '.result[0].message.chat.id'

If a token already exists at ~/.claude/.secrets/ccterrybot-telegram, verify it works and skip this phase.

Phase 3: Secrets Storage

Store the bot token securely:

mkdir -p ~/.claude/.secrets
chmod 700 ~/.claude/.secrets
echo "BOT_TOKEN=<token>" > ~/.claude/.secrets/ccterrybot-telegram
echo "CHAT_ID=<chat_id>" >> ~/.claude/.secrets/ccterrybot-telegram
chmod 600 ~/.claude/.secrets/ccterrybot-telegram

Create .mise.local.toml (gitignored) in the bot directory to load secrets:

# ~/.claude/automation/claude-telegram-sync/.mise.local.toml
[env]
_.file = "{{env.HOME}}/.claude/.secrets/ccterrybot-telegram"

Phase 4: Environment Configuration

Add Kokoro paths to mise.toml:

# In ~/.claude/automation/claude-telegram-sync/mise.toml [env] section
KOKORO_VENV = "{{env.HOME}}/.local/share/kokoro/.venv"
KOKORO_SCRIPT = "{{env.HOME}}/.local/share/kokoro/tts_generate.py"

Phase 5: Shell Symlinks

Create symlinks in ~/.local/bin/ pointing to plugin shell scripts:

mkdir -p ~/.local/bin
ln -sf <plugin>/scripts/tts_kokoro.sh ~/.local/bin/tts_kokoro.sh
ln -sf <plugin>/scripts/tts_read_clipboard.sh ~/.local/bin/tts_read_clipboard.sh
ln -sf <plugin>/scripts/tts_read_clipboard_wrapper.sh ~/.local/bin/tts_read_clipboard_wrapper.sh
ln -sf <plugin>/scripts/tts_speed_up.sh ~/.local/bin/tts_speed_up.sh
ln -sf <plugin>/scripts/tts_speed_down.sh ~/.local/bin/tts_speed_down.sh
ln -sf <plugin>/scripts/tts_speed_reset.sh ~/.local/bin/tts_speed_reset.sh

Phase 6: Verification

  1. Generate a test WAV and play it:
~/.local/share/kokoro/.venv/bin/python ~/.local/share/kokoro/tts_generate.py \
    --text "Hello, bootstrap complete." --voice af_heart --lang en-us --speed 1.0 --output /tmp/test-bootstrap.wav
afplay /tmp/test-bootstrap.wav
rm -f /tmp/test-bootstrap.wav
  1. Verify bot responds to /status via Telegram API:
curl -s "https://api.telegram.org/bot${BOT_TOKEN}/getMe" | jq .ok

TodoWrite Task Templates

Template: Full Stack Bootstrap

1. [Preflight] Verify Bun installed
2. [Preflight] Verify mise installed
3. [Preflight] Verify uv installed
4. [Preflight] Verify Python 3.13 available via uv
5. [Kokoro] Run kokoro-install.sh --install
6. [Kokoro] Verify MLX-Audio acceleration
7. [BotFather] Guide BotFather token creation (or verify existing)
8. [Secrets] Store token in ~/.claude/.secrets/ccterrybot-telegram
9. [Secrets] Create .mise.local.toml with _.file reference to secrets
10. [Environment] Add KOKORO_VENV and KOKORO_SCRIPT to mise.toml
11. [Symlinks] Create ~/.local/bin/ symlinks for all TTS shell scripts
12. [Verify] Generate test WAV with Kokoro and play with afplay
13. [Verify] Check bot responds to /status via Telegram API

Post-Change Checklist

After modifying this skill:

  1. Verify kokoro-install.sh --health passes all 6 checks
  2. Confirm .mise.local.toml is gitignored
  3. Test symlinks resolve correctly (ls -la ~/.local/bin/tts_*.sh)
  4. Verify bot token works via getMe API call
  5. Run a full TTS round-trip: clipboard text to audio playback
  6. Update references/evolution-log.md with change description

Troubleshooting

IssueCauseSolution
uv not foundNot installedbrew install uv
Python 3.13 not availableNot installed via uvuv python install 3.13
Not Apple SiliconIntel Mac or LinuxRequires M1 or newer Mac (MLX Metal)
Model download failsNetwork issue or HuggingFace outageCheck internet connectivity, retry
BotFather token invalidTypo or revoked tokenVerify via curl https://api.telegram.org/bot<TOKEN>/getMe
kokoro-install.sh permission deniedScript not executablechmod +x scripts/kokoro-install.sh
Venv already existsPrevious partial installRun kokoro-install.sh --uninstall then --install
tts_generate.py not foundBundle copy failedCheck scripts/tts_generate.py exists in plugin

Reference Documentation

Post-Execution Reflection

After this skill completes, reflect before closing the task:

  1. Locate yourself. — Find this SKILL.md's canonical path (Glob for this skill's name) before editing. All corrections target THIS file and its sibling references/ — never other documentation.
  2. What failed? — Fix the instruction that caused it. If it could recur, add it as an anti-pattern.
  3. What worked better than expected? — Promote it to recommended practice. Document why.
  4. What drifted? — Any script, reference, or external dependency that no longer matches reality gets fixed now.
  5. Log it. — Every change gets an evolution-log entry with trigger, fix, and evidence.

Do NOT defer. The next invocation inherits whatever you leave behind.



平台分布

Codex

34.38%
按下载量换算197

Claude

31.16%
按下载量换算179

Cursor

18.93%
按下载量换算109

Gemini CLI

8.7%
按下载量换算50

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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。

继续浏览同类 Skills