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Agent Skill · 研究检索

pypi-doppler(pypi 多普勒)

pypi-doppler 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。

pypi-doppler 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;许可证为 MIT,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 36,848。

总安装 1,853周安装 78GitHub Stars 38下载 649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
MIT

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:pypi-doppler(pypi 多普勒)
来源仓库:https://github.com/terrylica/cc-skills
仓库路径:skills/pypi-doppler
安装命令:
npx skills add https://github.com/terrylica/cc-skills --skill pypi-doppler
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/terrylica/cc-skills --skill pypi-doppler

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。

用于查找、检索和筛选相关信息。pypi-doppler 属于研究检索类 Skill,可作为该场景下的辅助能力补充。适合根据关键词或任务场景快速定位候选结果。通过 GitHub 安装,需结合原始 README 核验具体用法。安装前建议确认权限范围和维护状态。注意是否会触发联网、命令执行或文件读写操作。

来源仓库内路径:skills/pypi-doppler

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 pypi-doppler;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

pypi-doppler 怎么安装?

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

pypi-doppler 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。

pypi-doppler 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。

pypi-doppler 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

pypi-doppler 用的人多吗?

公开数据是累计安装 1,853 次,近一周安装 78 次,下载 649 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。

pypi-doppler 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。

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。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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
pypi-doppler

pypi 多普勒 · 本页

1,85338接触敏感数据MIT有提醒

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

PyPI Publishing with Doppler (Local-Only)

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

Use this skill when:

  • Publishing Python packages to PyPI from local machine
  • Setting up Doppler for PyPI token management
  • Creating local publish scripts with CI detection guards
  • Validating repository ownership before release

WORKSPACE-WIDE POLICY: LOCAL-ONLY PUBLISHING

This skill supports LOCAL machine publishing ONLY.

FORBIDDEN

  • Publishing from GitHub Actions
  • Publishing from any CI/CD pipeline (GitHub Actions, GitLab CI, Jenkins, CircleCI)
  • publishCmd in semantic-release configuration
  • Building packages in CI (uv build in prepareCmd)
  • Storing PyPI tokens in GitHub secrets

REQUIRED

  • Use scripts/publish-to-pypi.sh on local machine
  • CI detection guards in publish script
  • Manual approval before each release
  • Doppler credential management (no plaintext tokens)
  • Repository verification (prevents fork abuse)

Rationale

  • Security: No long-lived PyPI tokens in GitHub secrets
  • Speed: 30 seconds locally vs 3-5 minutes in CI
  • Control: Manual approval step before production release
  • Flexibility: Centralized credential management via Doppler

See: ADR-0027, docs/development/PUBLISHING.md


Overview

This skill provides local-only PyPI publishing using Doppler for secure credential management. It integrates with the workspace-wide release workflow where:

  1. GitHub Actions: Automated versioning ONLY (tags, releases, CHANGELOG)
  2. Local Machine: Manual PyPI publishing with Doppler credentials

Bundled Scripts

ScriptPurpose
scripts/publish-to-pypi.shLocal PyPI publishing with CI detection guards

Usage: Copy to your project's scripts/ directory:

/usr/bin/env bash << 'DOPPLER_EOF'
# Environment-agnostic path
PLUGIN_DIR="${CLAUDE_PLUGIN_ROOT:-$HOME/.claude/plugins/marketplaces/cc-skills/plugins/itp}"
cp "$PLUGIN_DIR/skills/pypi-doppler/scripts/publish-to-pypi.sh" scripts/
chmod +x scripts/publish-to-pypi.sh
DOPPLER_EOF

Prerequisites

One-Time Setup

  1. Install Doppler CLI: brew install dopplerhq/cli/doppler
  2. Authenticate with Doppler: doppler login
  3. Verify access to claude-config project: doppler whoami doppler projects

PyPI Token Setup

  1. Create PyPI API token:

- Visit: https://pypi.org/manage/account/token/ - Enable 2FA if not already enabled (required since 2024) - Create token with scope: "Entire account" or specific project - Copy token (starts with pypi-AgEIcHlwaS5vcmc..., ~180 characters)

  1. Store token in Doppler: doppler secrets set PYPI_TOKEN='pypi-AgEIcHlwaS5vcmc...' \ --project claude-config \ --config prd
  2. Verify token stored: doppler secrets get PYPI_TOKEN \ --project claude-config \ --config prd \ --plain

Publishing Workflow

MANDATORY: Verify Version Increment Before Publishing

Pre-publish validation: Before publishing to PyPI, verify that the version has incremented from the previous release. Publishing without a version increment is invalid and wastes resources.

Autonomous check sequence:

  1. Compare local pyproject.toml version against latest PyPI version
  2. If versions match -- STOP - do not proceed with publishing
  3. Inform user: "Version not incremented. Run semantic-release first or verify commits include feat: or fix: types."

Complete Release Workflow

Step 1: Development & Commit (Conventional Commits):

git add .
git commit -m "feat: add new feature"  # MINOR bump
git push origin main

Step 2: Automated Versioning (GitHub Actions - 40-60s):

GitHub Actions automatically: analyzes commits, determines next version, updates pyproject.toml/package.json, generates CHANGELOG, creates git tag, creates GitHub release.

PyPI publishing does NOT happen here (by design - see ADR-0027).

Step 3: Local PyPI Publishing (30 seconds):

git pull origin main
./scripts/publish-to-pypi.sh

Using Bundled Script (Recommended)

/usr/bin/env bash << 'GIT_EOF'
# First time: copy script from skill to your project (environment-agnostic)
PLUGIN_DIR="${CLAUDE_PLUGIN_ROOT:-$HOME/.claude/plugins/marketplaces/cc-skills/plugins/itp}"
cp "$PLUGIN_DIR/skills/pypi-doppler/scripts/publish-to-pypi.sh" scripts/
chmod +x scripts/publish-to-pypi.sh

# After semantic-release creates GitHub release
git pull origin main

# Publish using local copy of bundled script
./scripts/publish-to-pypi.sh
GIT_EOF

Bundled script features: CI detection guards, repository verification, Doppler integration, build + publish + verify workflow, clear error messages.

Manual Publishing (Advanced)

For manual publishing without the canonical script:

/usr/bin/env bash << 'CONFIG_EOF'
# Retrieve token from Doppler
PYPI_TOKEN=$(doppler secrets get PYPI_TOKEN \
  --project claude-config \
  --config prd \
  --plain)

# Build package
uv build

# Publish to PyPI
UV_PUBLISH_TOKEN="${PYPI_TOKEN}" uv publish
CONFIG_EOF

WARNING: Manual publishing bypasses CI detection guards and repository verification. Use canonical script unless you have a specific reason not to.


Reference Documentation

TopicReference
CI DetectionCI Detection Enforcement
Credential ManagementDoppler & Token Management
TroubleshootingTroubleshooting Guide
TestPyPI TestingTestPyPI Testing
mise Task Integrationmise Task Integration

Related Documentation

  • ADR-0027: docs/architecture/decisions/0027-local-only-pypi-publishing.md - Architectural decision for local-only publishing
  • ADR-0028: docs/architecture/decisions/0028-skills-documentation-alignment.md - Skills alignment with ADR-0027
  • PUBLISHING.md: docs/development/PUBLISHING.md - Complete release workflow guide
  • mise-tasks Skill: mise-tasks - Task orchestration with dependency management
  • Release Workflow Patterns: release-workflow-patterns.md - DAG patterns and anti-patterns
  • Bundled Script: scripts/publish-to-pypi.sh - Reference implementation with CI guards

Validation History

  • 2025-12-03: Refactored to discovery-first, environment-agnostic approach

- discover_uv() checks PATH, direct installs, version managers (priority order) - Supports: curl install, Homebrew, cargo, mise, asdf - doesn't force any method

  • 2025-11-22: Created with ADR-0027 alignment (workspace-wide local-only policy)
  • Validation: CI detection guards tested, Doppler integration verified

Last Updated: 2025-12-03 Policy: Workspace-wide local-only PyPI publishing (ADR-0027) Supersedes: None (created with ADR-0027 compliance from start)

Post-Execution Reflection

After this skill completes, check before closing:

  1. Did the command succeed? — If not, fix the instruction or error table that caused the failure.
  2. Did parameters or output change? — If the underlying tool's interface drifted, update Usage examples and Parameters table to match.
  3. Was a workaround needed? — If you had to improvise (different flags, extra steps), update this SKILL.md so the next invocation doesn't need the same workaround.

Only update if the issue is real and reproducible — not speculative.

平台分布

Claude Code

28.39%
按下载量换算184

OpenCode

24.53%
按下载量换算159

Antigravity

18.33%
按下载量换算119

Gemini CLI

12.85%
按下载量换算83

windsurf

7.15%
按下载量换算46

trae

3.55%
按下载量换算23

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。

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