Token导航 LogoToken导航TokenDH.com
研究检索操作浏览器clawhub未标认证来源可访问clear审计提醒

pain-to-pip-package痛苦到点包

Agent Skill

pain-to-pip-package 用于查找、检索和筛选相关信息,适合在 OpenClaw 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。

总安装

1,529

周安装

65

GitHub Stars

公开资料未说明

下载量

536
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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:pain-to-pip-package(痛苦到点包)
来源仓库:https://github.com/minirr890112-byte/pain-to-pip-package
安装命令:
openclaw skills install pain-to-pip-package
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install pain-to-pip-package

简介

从 Reddit 疼痛信号构建可安装 CLI 工具的全流程管道。

  • 已成功交付 5 个工具,经 343 个案例验证。
  • 自动完成扫描→集群→打包→推送 GitHub 环节。
  • 输出物为标准 pip 包,可直接部署使用。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。
  • pain-to-pip-package 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
pain-to-pip-package
version
0.1.0
description
>-
category
product

Pain-to-Pip-Package Pipeline

End-to-end workflow for turning Reddit complaints into standalone pip-installable CLI tools.

When to use

  • You've scanned Reddit and found a recurring pain point (≥3 signals)
  • You want to build a tool that solves it
  • You want the tool discoverable via GitHub search
  • You want it pip-installable as a standalone package

Pipeline Steps

1. Scan Reddit for pain signals

python3 scripts/daily-pipeline run

Uses Reddit's public .json API (no auth needed for reading). Key lessons:

  • Pushshift is dead (403 Forbidden) — use reddit.com/r/{sub}/hot.json directly
  • Rate limits: 429 errors after ~5 subs. Keep SCAN_TIMEOUT ≤ 8s, sleep 0.5s between requests
  • 5 subreddits max for <2 minute scans. More = diminishing returns + rate limits
  • Use a realistic User-Agent header

2. Classify pain signals into clusters

Keywords-based clustering into 8 categories:

  • AI Censorship / Safety Overreach
  • AI Model Degradation
  • AI API Pricing / Cost
  • GitHub / CI-CD Issues
  • AI Code Quality
  • Local LLM / Deployment
  • Supply Chain Security
  • AI Detection / Deepfake

Existing tools are matched via keyword map to avoid duplicates.

3. Build the tool as a standalone pip package

Every tool follows this structure:

tool-name/
  pyproject.toml         # setuptools.build_meta, entry point
  README.md              # install + usage + pain source quote
  tool_package/
    __init__.py          # from .cli import main; __version__
    cli.py               # all logic, main() at bottom

pyproject.toml template:

[build-system]
requires = ["setuptools>=64", "wheel"]
build-backend = "setuptools.build_meta"

[project]
name = "tool-name"
version = "0.1.0"
description = "..."
readme = "README.md"
license = {text = "MIT"}
requires-python = ">=3.8"
keywords = ["relevant", "search", "terms"]
urls = { repository = "https://github.com/OWNER/REPO" }

[project.scripts]
tool-command = "tool_package.cli:main"

[tool.setuptools.packages.find]
include = ["tool_package*"]

CRITICAL: build-backend must be "setuptools.build_meta" NOT "setuptools.backends._legacy:_Backend". The latter causes BackendUnavailable on pip install.

4. Test the install

pip install --break-system-packages ./tool-name
tool-command  # verify entry point works

5. Push + Release

git add tool-name/
git commit -m "feat: tool-name — description"
git push
gh release create vX.Y.Z --title "vX.Y.Z — N Tools" --notes "..."

6. Update root README

  • Add tool to the Tools section with demo output
  • Update install section with new pip command
  • Update roadmap table
  • Add stars badge: ![Stars](https://img.shields.io/github/stars/OWNER/REPO)

Pitfalls

  1. Never use execute_code to read+write files in the same scriptread_file returns line-numbered content like 1|content. If you pass that to write_file, the file gets literal 1| prefixes, breaking TOML parsers.
  1. Reddit browser access blocked — Cloud browsers get "blocked by network security" on Reddit. Only API access works. Posting requires user credentials (praw or OAuth).
  1. pip in newer macOS — Use --break-system-packages flag or create venvs.
  1. GitHub topic limit — 20 topics max. Remove generic ones (tools, productivity) to make room for search-specific ones.

SEO: Making tools discoverable

GitHub search indexes: repo name, description, topics, README content (lower weight).

Description formula: "AI CLI tools: [keyword1] & [keyword2], [keyword3] & [keyword4], [keyword5] for [providers]. [unique hook]."

Example: "AI CLI tools: prompt censorship checker & bypass, model quality watchdog & degradation monitor, API cost comparison for OpenAI Claude DeepSeek Gemini. Built from real Reddit user complaints."

Topics: Prioritize search-intent keywords over generic ones. Every topic is a search facet.

Validation: After updating, search GitHub for the exact phrases users would type. Verify the repo appears in top 3.

Daily Automation

Two cron jobs drive continuous improvement:

  1. daily-reddit-pipeline (8:00 AM): scan → classify → report → push to GitHub
  2. github-metrics-daily (9:00 AM): record stars/views/search rankings

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

79.61%
按下载量换算427

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

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。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills