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Agent Skill · 研究检索

scaffold-github-cloud-agent-environment(scaffold GitHub cloud Agent environment 搜索)

用于围绕 GitHub 仓库、Issue、Pull Request、分支、提交和代码协作流程提供辅助能力。它适合让 Agent 查询项目状态、整理变更、辅助创建或检查协作事项,并把仓库中的信息转成可执行的下一步。使用时需要区分只读查询和写入操作;涉及创建 PR、修改 Issue、推送分支或访问私有仓库时,应确认 token 权限、目标仓库范围和用户授权。

scaffold-github-cloud-agent-environment 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 73,675 个 Skill 里排第 71,838。

总安装 192周安装 8GitHub Stars 13下载 64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:scaffold-github-cloud-agent-environment(scaffold GitHub cloud Agent environment 搜索)
来源仓库:https://github.com/jpcaparas/skills
仓库路径:skills/scaffold-github-cloud-agent-environment
安装命令:
npx skills add https://github.com/jpcaparas/skills --skill scaffold-github-cloud-agent-environment
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/jpcaparas/skills --skill scaffold-github-cloud-agent-environment

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。

该技能围绕 GitHub 仓库协作流程提供辅助能力,支持 Issue、PR 和分支管理。适合查询项目状态、整理变更记录或生成可执行协作事项。通过 npx skills add 命令从 jpcaparas/skills 仓库安装调用。区分只读查询与写入操作,涉及私有仓库时需确认 token 权限范围。

建议结合用户授权与目标仓库策略控制操作边界。

来源仓库内路径:skills/scaffold-github-cloud-agent-environment

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/jpcaparas/skills --skill scaffold-github-cloud…;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

scaffold-github-cloud-agent-environment 怎么安装?

在终端执行 npx skills add https://github.com/jpcaparas/skills --skill scaffold-github-cloud-agent-env…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

scaffold-github-cloud-agent-environment 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。

scaffold-github-cloud-agent-environment 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。

scaffold-github-cloud-agent-environment 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。

scaffold-github-cloud-agent-environment 用的人多吗?

公开数据是累计安装 192 次,近一周安装 8 次,下载 64 次,GitHub 13 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。

scaffold-github-cloud-agent-environment 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
scaffold-github-cloud-agent-environment

scaffold GitHub cloud Agent environment 搜索 · 本页

19213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

scaffold-github-cloud-agent-environment

Audit the target repository first, then scaffold or repair GitHub Copilot cloud agent's development environment around the current live GitHub Docs contract.

Decision Tree

What is the user asking for?

  • No .github/workflows/copilot-setup-steps.yml exists yet: Verify the live docs, audit the repo, draft a plan, ask only the targeted questions that repo signals cannot answer, then scaffold the workflow.
  • A copilot-setup-steps.yml file already exists but looks thin, stale, or incorrect: Audit what is there, compare it to the live docs, choose refresh mode, and regenerate a deterministic workflow that preserves the documented contract.
  • Agent runs fail or behave strangely after scaffolding: Run doctor mode first, use session-log evidence and repo facts to identify whether the fix is in-repo or in GitHub settings, then patch only what the evidence supports.
  • The user only wants explanation or planning: Read references/live-docs.md, references/project-analysis.md, references/patterns.md, and references/doctor-mode.md, then answer without scaffolding.

Quick Reference

TaskAction
Verify the live GitHub contract firstRead the URLs in references/live-docs.md
Audit a target repositoryRun scripts/audit_project.sh /path/to/project
Draft a plan from repo factsRun python3 scripts/suggest_plan.py --project /path/to/project
Render or refresh the workflowRun python3 scripts/render_setup_workflow.py --project /path/to/project --plan /path/to/plan.json
Diagnose an existing setupRun python3 scripts/doctor.py --project /path/to/project --symptom "describe the failure" --json
Understand repo questions to ask before writing filesRead references/project-analysis.md
Choose ecosystem-specific dependency stepsRead references/patterns.md
Map symptoms to fixesRead references/doctor-mode.md

Non-Negotiable Workflow

  1. Re-check the live official GitHub docs before every real scaffold or repair. Do not trust a stale memory of the feature.
  2. Audit the repository before choosing steps, runners, or environment assumptions.
  3. Distinguish repo-local fixes from GitHub settings fixes:

- repo-local: .github/workflows/copilot-setup-steps.yml, .github/copilot-instructions.md, package-manager setup, LFS checkout, service containers - settings-level: runner policy, firewall allowlist, workflow approval, copilot environment secrets or variables

  1. Keep project-specific judgment in the plan JSON, not buried inside the renderer.
  2. Ask targeted questions when ambiguity matters. Typical blockers are:

- the repo signals Windows, but the requirement is not explicit - multiple package managers or multiple toolchains compete - private registries or internal hosts are present - self-hosted or larger runners may be required - tests depend on services that are not obviously expressible as GitHub Actions services

  1. Keep the workflow anchored to .github/workflows/copilot-setup-steps.yml with one job named copilot-setup-steps.
  2. Only rely on documented job keys for that job: steps, permissions, runs-on, services, snapshot, and timeout-minutes.
  3. Treat setup-step failures as degraded environments, not hard stops. The docs say Copilot skips the remaining setup steps and continues with whatever environment exists at that point.
  4. Default to deterministic dependency installation. Let Copilot discover build and validation commands through custom instructions and repo context, not trial-and-error dependency bootstrapping.
  5. In doctor mode, start with session logs and the observed symptom. Do not guess at fixes that the logs or repo facts do not support.

Live Docs First

The official GitHub Docs pages below are the source of truth. Read them before real work:

  • https://docs.github.com/en/copilot/how-tos/use-copilot-agents/cloud-agent/customize-the-agent-environment
  • https://docs.github.com/en/copilot/how-tos/use-copilot-agents/cloud-agent/customize-the-agent-firewall
  • https://docs.github.com/en/copilot/how-tos/administer-copilot/manage-for-organization/configure-runner-for-coding-agent
  • https://docs.github.com/en/copilot/how-tos/use-copilot-agents/cloud-agent/troubleshoot-cloud-agent
  • https://docs.github.com/en/copilot/how-tos/use-copilot-agents/cloud-agent/track-copilot-sessions
  • https://docs.github.com/en/copilot/how-tos/use-copilot-agents/cloud-agent/configuring-agent-settings
  • https://docs.github.com/en/copilot/tutorials/cloud-agent/get-the-best-results
  • https://docs.github.com/actions/using-workflows/workflow-syntax-for-github-actions

Use references/live-docs.md for the purpose of each URL and the exact moments you must re-open it.

Project Analysis Rules

Before you write or replace copilot-setup-steps.yml, inspect:

  • whether .github/workflows/copilot-setup-steps.yml already exists
  • package managers, lockfiles, and toolchain version files
  • CI workflows and any existing runner choices
  • .github/copilot-instructions.md, .github/instructions/**/*.instructions.md, AGENTS.md, CLAUDE.md, and GEMINI.md
  • .gitattributes for Git LFS usage
  • .devcontainer/, Dockerfiles, Compose files, and service requirements
  • private-registry config files such as .npmrc, .yarnrc.yml, pip.conf, .pypirc, .cargo/config.toml, nuget.config, or settings.xml
  • Windows-only or internal-network signals

Run scripts/audit_project.sh first, then read references/project-analysis.md when you need the full checklist and the question set.

Deterministic Versus Heuristic Work

Keep these parts deterministic:

  • the workflow path and job name
  • the documented job-key allowlist
  • timeout-minutes staying at or below 59
  • validation triggers for easy manual and PR testing
  • low-privilege permissions
  • LFS enablement when the repo clearly uses Git LFS
  • the doctor checks for missing workflow, wrong job name, unsupported job keys, missing checkout, and settings-only failure modes

Allow these parts to stay heuristic, but surface the assumptions:

  • which runner strategy fits the repo
  • whether the workflow should set up one toolchain or several
  • exact dependency install commands
  • whether service containers are safe to express in services
  • whether the repo needs repo-level or org-level firewall or runner changes

If a heuristic choice can materially change correctness, add it to questions and ask the user instead of silently guessing.

Repeat-Run Rules

When the skill is invoked again against a project:

  • Re-verify the live docs before assuming the contract is unchanged.
  • Re-audit the repo before assuming the existing plan still fits.
  • If the workflow already exists, default to refresh mode and back up the current file before replacement.
  • Preserve the required job name and path on every refresh.
  • Prefer improving a weak setup over adding second competing setup files.
  • Use doctor mode first when the user reports failures from a real agent run.

Scaffold Rules

  • Write .github/workflows/copilot-setup-steps.yml, not a generic setup workflow under another name.
  • Keep exactly one job named copilot-setup-steps.
  • Only use supported job keys in that job.
  • Keep timeout-minutes at 59 or lower.
  • Add workflow_dispatch, push, and pull_request triggers scoped to the workflow file unless the user explicitly wants a quieter validation pattern.
  • Add contents: read when the workflow checks out the repository.
  • If the repo uses Git LFS, use actions/checkout@v5 with lfs: true.
  • Do not rely on a custom fetch-depth value. The live docs say Copilot overrides it.
  • For self-hosted runners, require the user to disable the integrated firewall and allow the documented GitHub and Copilot hosts.
  • For Windows runners, treat network controls as an explicit design decision because the integrated firewall is not compatible with Windows.
  • Put secrets and environment variables in the copilot environment, not inline in the workflow.
  • Treat .github/copilot-instructions.md as a companion file whenever Copilot needs clear build, test, or validation commands.

Doctor Mode

Doctor mode is for real failures after a scaffold or for repos with questionable existing setups.

Run python3 scripts/doctor.py --project /path/to/project --symptom "what failed" --json, then use the findings to decide the next action:

  • local workflow fix: regenerate or patch copilot-setup-steps.yml
  • repo settings fix: update firewall or workflow-approval settings
  • org settings fix: runner defaults or repository override policy
  • session investigation: inspect the live session logs before changing files

Read references/doctor-mode.md for the symptom map and references/gotchas.md for the less obvious traps.

Reading Guide

NeedRead
Official URLs and refresh policyreferences/live-docs.md
What to inspect before choosing steps or runnersreferences/project-analysis.md
Generated file layout and plan JSON shapereferences/scaffold-layout.md
Ecosystem setup patterns and when to ask questionsreferences/patterns.md
Session-log-led troubleshootingreferences/doctor-mode.md
Default-branch, firewall, workflow-approval, and runner trapsreferences/gotchas.md

Operational Scripts

  • scripts/audit_project.sh inspects a target repo and reports environment-relevant facts as JSON.
  • scripts/suggest_plan.py turns repo facts into a draft plan with assumptions, manual settings, and questions.
  • scripts/render_setup_workflow.py renders or refreshes .github/workflows/copilot-setup-steps.yml from an explicit plan.
  • scripts/doctor.py diagnoses existing setup issues and separates repo changes from GitHub settings changes.
  • scripts/validate.py checks structure, cross-references, and required support files.
  • scripts/test_skill.py runs lightweight syntax and integration checks against temp repositories.

Gotchas

  1. The workflow only matters once it exists on the default branch. A correct file on a feature branch is still inert for real Copilot runs.
  2. The live docs say only steps, permissions, runs-on, services, snapshot, and timeout-minutes are honored in the copilot-setup-steps job. Extra job keys may look valid but be ignored.
  3. If a setup step exits non-zero, Copilot skips the remaining setup steps and continues anyway.
  4. Self-hosted runners require the integrated firewall to be disabled in repository settings.
  5. Windows runners are not compatible with the integrated firewall.
  6. Organization-level runner policy can silently override a repository's preferred runs-on.
  7. GitHub Actions workflows do not run automatically when Copilot pushes unless a human approves them or repository settings allow automatic runs.
  8. actions/checkout fetch-depth is overridden by Copilot's platform behavior, so do not depend on a custom shallow-clone depth.
  9. The firewall only applies to processes started by the agent in the Actions appliance. It does not protect setup steps or MCP servers.
  10. If the repo depends on private registries or internal hosts, the real fix is usually a combination of copilot environment secrets or variables plus firewall or runner changes, not only a YAML edit.

平台分布

Codex

35.19%
按下载量换算23

Claude

31.44%
按下载量换算20

Cursor

20.67%
按下载量换算13

Gemini CLI

9.28%
按下载量换算6

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。

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