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render-deploy渲染部署

Agent Skill

用于辅助云资源、部署、容器、基础设施和运维自动化任务。它适合让 Agent 检查配置、整理部署步骤、分析资源状态、生成排障思路或辅助云服务接入。使用时需要明确目标环境、账号权限、区域和资源组,区分本地测试与生产操作;涉及删除资源、重启服务、修改网络或权限配置时,应先确认影响范围。

总安装

16,608

周安装

692

GitHub Stars

公开资料未说明

下载量

5,536
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:render-deploy(渲染部署)
来源仓库:https://github.com/ivangdavila/render-deploy
安装命令:
openclaw skills install render-deploy
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 render-deploy

简介

通过代码库分析、render.yaml 蓝图生成、MCP 直接配置和部署后验证在 Render 上部署应用程序。

SKILL.md

name
Render Deploy
slug
render-deploy
version
1.0.0
homepage
https://clawic.com/skills/render-deploy
description
Deploy applications on Render with codebase analysis, render.yaml Blueprint generation, MCP direct provisioning, and post-deploy verification.
changelog
Added end-to-end Render deployment guidance with method selection, runtime checks, and practical troubleshooting flows.
metadata
{"clawdbot":{"emoji":"🚀","requires":{"bins":["git","render"],"env":["RENDER_API_KEY"],"config":["~/render-deploy/"]},"primaryEnv":"RENDER_API_KEY","install":[{"id":"brew","kind":"brew","formula":"render","bins":["render"],"label":"Install Render CLI (Homebrew)"}],"os":["linux","darwin","win32"]}}

Setup

On first use, read setup.md for integration guidelines. If local memory is needed, ask for consent before creating ~/render-deploy/.

When to Use

Use this skill when the user wants to deploy, publish, or host an application on Render and needs reliable deployment execution instead of generic advice. Activate for render.yaml Blueprint generation, MCP direct service creation, runtime configuration checks, and post-deploy triage.

Architecture

Memory lives in ~/render-deploy/. See memory-template.md for setup.

~/render-deploy/
|- memory.md                  # Stable preferences and integration choices
|- deployment-notes.md        # Project-level deployment decisions
|- env-inventory.md           # Required env vars and source of truth
`- incident-log.md            # Deploy failures and resolved fixes

Quick Reference

Load only the minimum file needed for the current request.

TopicFile
Setup processsetup.md
Memory templatememory-template.md
Codebase detection and commandscodebase-analysis.md
Blueprint workflow and render.yaml rulesblueprint-workflow.md
Authentication and MCP execution mappingdirect-creation.md
Startup and healthcheck troubleshootingtroubleshooting.md

Authentication Model

Before any provisioning command, confirm one of these is active:

  • RENDER_API_KEY is exported in the shell, or
  • Render CLI is authenticated (render whoami -o json)

For git-backed flows, require git and a valid remote URL. Do not attempt opaque credential discovery or unrelated environment inspection.

Core Rules

1. Classify the Deployment Path First

Before proposing commands, decide which path applies:

  • Git-backed deploy (Blueprint or Direct Creation)
  • Prebuilt Docker image deploy via Dashboard/API

If the repository has no remote, stop and ask the user to push a remote or switch to dashboard image deploy.

2. Choose Method by Complexity, Not Preference

Default decision:

  • Direct Creation when it is one simple service and no extra infra
  • Blueprint when there are multiple services, datastores, cron, workers, or reproducibility requirements

If uncertainty remains, ask one clarifying question and continue.

3. Verify Prerequisites Before Any Deploy Action

Run checks in this order:

  • git remote -v for source availability
  • MCP availability (list_services())
  • CLI fallback readiness (render --version, render whoami -o json)
  • Active workspace context (MCP or CLI)
  • Authentication presence (RENDER_API_KEY or authenticated CLI session)

Do not proceed to deployment steps when prerequisites are missing.

4. Treat render.yaml as Executable Infrastructure

When using Blueprint:

  • Declare all required env vars
  • Mark user-provided secrets with sync: false
  • Prefer plan: free unless user requests another plan
  • Match service type and runtime to the actual app behavior

After creating the file, validate before push.

5. Require Push Before Deeplink Handoff

Before sharing a Render Blueprint deeplink, confirm render.yaml is committed and pushed to the remote branch. If not pushed, the Dashboard flow will fail to discover the configuration.

6. Verify the Deployment and Close With Evidence

After deployment:

  • Confirm latest deploy status is live
  • Check health endpoint response
  • Review recent error logs
  • Validate required env vars and port binding (0.0.0.0:$PORT)

If failures exist, run one-fix-at-a-time triage from troubleshooting.md.

Common Traps

  • Starting deploy without a git remote -> Blueprint and MCP git-backed flows fail immediately.
  • Picking Direct Creation for multi-service systems -> Missing workers/datastores and fragmented setup.
  • Forgetting sync: false on secrets -> Broken deploys or accidental secret exposure in config.
  • Using localhost binding instead of 0.0.0.0:$PORT -> Health checks fail even when process is running.
  • Redeploying repeatedly without root-cause fix -> Noisy failures and delayed resolution.

External Endpoints

EndpointData SentPurpose
https://dashboard.render.comRepository URL, service config, env key namesBlueprint apply flow and dashboard provisioning
https://mcp.render.comService creation/config requests and workspace-scoped metadataMCP direct provisioning
https://api.render.comDeployment metadata, logs, service status (via CLI/API)Validation and operational checks

No other endpoints should be used unless the user requests an explicit integration.

Security & Privacy

Data that leaves your machine:

  • Repository URL and deployment metadata sent to Render services.
  • Environment variable names and provided values when the user explicitly sets them.

Data that stays local:

  • Preferences and deployment history in ~/render-deploy/ if the user accepts memory.
  • Local codebase inspection outputs and interim analysis notes.

This skill does NOT:

  • Read unrelated credentials outside the deployment context.
  • Scrape credentials from shell history, dotfiles, or unrelated config paths.
  • Send project files to undeclared third-party endpoints.
  • Run destructive infrastructure changes without explicit confirmation.

Trust

By using this skill, deployment metadata and selected configuration are sent to Render services. Only use it if you trust Render with this operational data.

Related Skills

Install with clawhub install <slug> if user confirms:

  • deploy - General deployment planning and release execution.
  • devops - CI/CD, infrastructure workflows, and ops coordination.
  • docker - Container packaging and runtime configuration.
  • ci-cd - Pipeline automation and release validation stages.
  • nodejs - Runtime-specific app configuration and startup tuning.

Feedback

  • If useful: clawhub star render-deploy
  • Stay updated: clawhub sync

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

97.16%
按下载量换算5,379

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

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。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。

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