How do I install the Infra Deployment Debugging skill?

Run npx skillmds@latest add tuyv/infra-deployment-debugging in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Infra Deployment Debugging safe to use?

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Which AI agents work with Infra Deployment Debugging?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Infra Deployment Debugging free to use?

Yes. Installing skills from SkillMD is free. This skill is licensed under Apache-2.

Who published Infra Deployment Debugging?

tuyv (@tuyv) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Infra Deployment Debugging by tuyv — Agent Skill

Name: Infra Deployment Debugging
Author: tuyv

Infra Deployment Debugging

Troubleshoots infrastructure deployment failures. Use when analyzing deployment failures of ADC applications or direct/raw Terraform deployment errors. Don't use for design, local validation, plan assessment, or non-deployment troubleshooting.

tuyv f87ae4a 4 files · 9.1 KB Updated Sep 17, 2026

File contents

Deployment Troubleshooting Skill

Use this skill to analyze and resolve deployment failures. This skill supports troubleshooting:

ADC Applications: High-level designs deployed in Application Design Center.
Raw Terraform (TF): Infrastructure configurations managed directly via Terraform HCL files.

Constraints

Use standard tools: All interactions with GCP must be performed using standard commands (e.g., gcloud, terraform). Do not use custom internal backend APIs.
No Real Deployments: NEVER run mutating deployment commands (e.g., gcloud design-center spaces applications deploy or terraform apply) under any circumstances, as this is a read-only validation and dry-run troubleshooting workflow.
Read-Only Discovery: Do not run mutating commands during discovery. Discovery must be strictly read-only.
Strict Step Adherence: You MUST execute all steps in the chosen troubleshooting template in sequence. Do NOT skip steps or jump directly to remediation, even if the error seems obvious. Every step (e.g., init, validate, plan, or describes/logs fetches) must be executed and their outputs verified.

Troubleshooting Process (Progressive Disclosure)

To begin, you must determine the appropriate troubleshooting context based on the user's input.

Step 1: Determine the Entry Point

Evaluate the input provided by the user:

Case A: ADC Application Deployment:
- Indicator: The input contains an application_uri (e.g., projects/P/locations/L/spaces/S/applications/A) or references an App Design Center context.
- Act: Read and follow the detailed instructions in adc_application_troubleshooting.md to complete the troubleshooting task.
Case B: Raw Terraform Deployment:
- Indicator: The input contains raw Terraform configuration code (HCL contents), .tf files, or direct Terraform plan/apply execution errors.
- Act: Read and follow the detailed instructions in raw_terraform_troubleshooting.md to complete the troubleshooting task.

Reporting Issues

Report bugs or improvements for this skill at Google Skills Issues.

---name: infra-deployment-debuggingdescription: Troubleshoots infrastructure deployment failures. Use when analyzing deployment failures of ADC applications or direct/raw Terraform deployment errors. Don't use for design, local validation, plan assessment, or non-deployment troubleshooting.license: Apache-2.0---# Deployment Troubleshooting SkillUse this skill to analyze and resolve deployment failures. This skill supportstroubleshooting:1. **ADC Applications**: High-level designs deployed in Application Design Center.2. **Raw Terraform (TF)**: Infrastructure configurations managed directly via Terraform HCL files.## Constraints- **Use standard tools**: All interactions with GCP must be performed using standard commands (e.g., `gcloud`, `terraform`). Do not use custom internal backend APIs.- **No Real Deployments**: NEVER run mutating deployment commands (e.g., `gcloud design-center spaces applications deploy` or `terraform apply`) under any circumstances, as this is a read-only validation and dry-run troubleshooting workflow.- **Read-Only Discovery**: Do not run mutating commands during discovery. Discovery must be strictly read-only.- **Strict Step Adherence**: You MUST execute all steps in the chosen troubleshooting template in sequence. Do NOT skip steps or jump directly to remediation, even if the error seems obvious. Every step (e.g., init, validate, plan, or describes/logs fetches) must be executed and their outputs verified.## Troubleshooting Process (Progressive Disclosure)To begin, you must determine the appropriate troubleshooting context based onthe user's input.### Step 1: Determine the Entry PointEvaluate the input provided by the user:- **Case A: ADC Application Deployment**: * **Indicator**: The input contains an `application_uri` (e.g., `projects/P/locations/L/spaces/S/applications/A`) or references an App Design Center context. * **Act**: Read and follow the detailed instructions in [adc_application_troubleshooting.md](templates/adc_application_troubleshooting.md) to complete the troubleshooting task.- **Case B: Raw Terraform Deployment**: * **Indicator**: The input contains raw Terraform configuration code (HCL contents), `.tf` files, or direct Terraform plan/apply execution errors. * **Act**: Read and follow the detailed instructions in [raw_terraform_troubleshooting.md](templates/raw_terraform_troubleshooting.md) to complete the troubleshooting task.## Reporting IssuesReport bugs or improvements for this skill at [Google Skills Issues](https://github.com/google/skills/issues).

Frequently asked questions