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Agent skill

Research To Deploy

by jeremylongshore in jeremylongshore/tons-of-skills-marketplace

Researches infrastructure best practices and generates deployment-ready configurations, Terraform modules, Dockerfiles, and CI/CD pipelines.

MITAuto-check passedDevOps & Cloud

Install Research To Deploy

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill research-to-deploy -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace research-to-deploy --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/research-to-deploy .claude/skills/research-to-deploy && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
research-to-deploy
GitHub stars
2.8k
Token cost
~1.8k tokens
SKILL.md length
789 words
Files
1
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Researches infrastructure best practices and generates deployment-ready configurations, Terraform modules, Dockerfiles, and CI/CD pipelines.

  • Works in 5 steps: Describe what you want to deploy and where → Specify constraints if you have them → Let the skill research. It will search… → …
  • The user needs to deploy services
  • SKILL.md covers Overview, Instructions, Output and Examples, plus 3 more sections
  • Calls terraform, docker and kubectl

What it does

Research To Deploy is an agent skill from jeremylongshore/tons-of-skills-marketplace. Researches infrastructure best practices and generates deployment-ready configurations, Terraform modules, Dockerfiles, and CI/CD pipelines. Use when the user needs to deploy services, set up infrastructure, or create cloud configurations based on current best practices. Trigger with phrases like "research and deploy", "set up Cloud Run", "create Terraform for", "deploy this to AWS", or "generate infrastructure configs".

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: Designed for Claude Code

It sits in DevOps & Cloud, covering Infrastructure as code, Deployment and Containers. It works with Amazon Web Services, Terraform, Cloud Run and Google Cloud. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.

When your agent uses it

  • The user needs to deploy services
  • Set up infrastructure
  • Create cloud configurations based on current best practices
  • With phrases like research and deploy

Example prompts

  • “research and deploy”
  • “set up Cloud Run”
  • “create Terraform for”
  • “/research-to-deploy”

Requirements

  • Python 3
  • Node.js
  • Docker
  • Compatibility (from SKILL.md): Designed for Claude Code
  • Pre-approved tools (allowed-tools): Read, Write, Edit, Bash(terraform:*), Bash(docker:*), Bash(kubectl:*), Bash(git:*), Bash(npm:*), Glob, Grep, WebSearch, WebFetch

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Describe what you want to deploy and where
  2. Specify constraints if you have them
  3. Let the skill research. It will search for current documentation, community best practices, and known pitfalls for the specified platform…
  4. Review the research summary and confirm the approach. The skill presents
  5. Apply the generated configs after review

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Bash(terraform:*)
    • Bash(docker:*)
    • Bash(kubectl:*)
    • Bash(git:*)
    • Bash(npm:*)
    • Glob
    • Grep

    …and 2 more on the same allowed-tools line.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • terraform
    • docker
    • kubectl

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • registry.terraform.io
    • aws.amazon.com
    • cloud.google.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Designed for Claude Code

    From compatibility in the SKILL.md frontmatter.

Context cost

Research To Deploy loads about 1.8k tokens when it runs. Until then it costs about 111 tokens; SKILL.md has 789 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~111
When it runs · the whole SKILL.md, loaded when a task matches
~1.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 789 words, ~1,757 tokens.

Download SKILL.mdSave it as .claude/skills/research-to-deploy/SKILL.md (or your agent's skills folder).
name
research-to-deploy
description
Researches infrastructure best practices and generates deployment-ready configurations, Terraform modules, Dockerfiles, and CI/CD pipelines. Use when the user needs to deploy services, set up infrastructure, or create cloud configurations based on current best practices. Trigger with phrases like "research and deploy", "set up Cloud Run", "create Terraform for", "deploy this to AWS", or "generate infrastructure configs".
allowed-tools
Read, Write, Edit, Bash(terraform:*), Bash(docker:*), Bash(kubectl:*), Bash(git:*), Bash(npm:*), Glob, Grep, WebSearch, WebFetch
compatibility
Designed for Claude Code
version
0.14.0
author
Jeremy Longshore <jeremy@intentsolutions.io>
license
MIT
tags
deployment, infrastructure, automation, devops, terraform, cloud

Research to Deploy

Research infrastructure best practices and generate deployment-ready cloud configurations.

Overview

This skill bridges the gap between researching cloud infrastructure patterns and actually deploying them. Instead of spending hours reading documentation, comparing approaches, and manually writing configuration files, this skill automates the entire pipeline: it searches for current best practices on the target platform, synthesizes the findings into a coherent deployment strategy, and generates production-grade Infrastructure as Code (IaC) that you can review and apply directly.

The skill supports multi-cloud deployments across GCP, AWS, and Azure, as well as platform-as-a-service providers like Railway, Fly.io, and Render. It generates Terraform modules by default but can also produce Pulumi programs, Docker Compose files, Kubernetes manifests, or platform-specific CLI commands. Every generated configuration includes security hardening, monitoring hooks, and cost optimization annotations based on the latest recommendations from the cloud provider.

Instructions

  1. Describe what you want to deploy and where:

    • "Research GCP Cloud Run best practices and deploy my Node.js API to staging"
    • "Set up a production Kubernetes cluster on AWS with monitoring"
    • "Create Terraform configs for a serverless Python function on Azure"

  2. Specify constraints if you have them:

    • Budget: "keep monthly costs under $50"
    • Region: "deploy to us-central1"
    • Compliance: "needs HIPAA-compliant storage"
    • Existing infra: "we already use Terraform Cloud for state management"

  3. Let the skill research. It will search for current documentation, community best practices, and known pitfalls for the specified platform and service. The research phase produces a summary of findings before generating any code.

  4. Review the research summary and confirm the approach. The skill presents:

    • Recommended architecture with rationale
    • Cost estimate based on expected usage
    • Security considerations and mitigations
    • Alternative approaches that were considered

  5. Apply the generated configs after review:

    • Terraform: terraform init && terraform plan
    • Docker: docker compose up -d
    • Kubernetes: kubectl apply -f

Output

The skill produces a structured set of deployment artifacts:

  • Research Summary (Markdown): A concise document covering the best practices found, architectural decisions made, and trade-offs considered. Includes source links.
  • Infrastructure Code: Terraform modules (.tf files), Dockerfiles, Kubernetes manifests, or platform-specific configs organized in a standard directory structure.
  • CI/CD Pipeline: GitHub Actions workflow or equivalent CI config that automates testing, building, and deploying the infrastructure.
  • Monitoring Setup: Configuration for health checks, alerting rules, and dashboards appropriate to the target platform (Cloud Monitoring, CloudWatch, or Datadog).
  • Cost Estimate: Annotated breakdown of expected monthly costs based on the chosen resources and expected traffic.
  • Runbook (Markdown): Step-by-step instructions for deploying, updating, rolling back, and troubleshooting the infrastructure.

Examples

Example 1: GCP Cloud Run Deployment

User: "Research Cloud Run best practices and create a deployment for my Express API."

The skill will:

  1. Search for current Cloud Run documentation on container sizing, concurrency settings, min/max instances, and VPC connector patterns.
  2. Generate a Dockerfile optimized for Cloud Run (multi-stage build, non-root user, health check endpoint).
  3. Create main.tf with Cloud Run service, IAM bindings, custom domain mapping, and Cloud SQL connection.
  4. Add a GitHub Actions workflow for automated deployment on push to main.
  5. Include a monitoring.tf with uptime checks and alerting policies.
Show full SKILL.md (278 more words)Show less
Example 2: AWS ECS Fargate with Terraform

User: "Deploy a Python microservice to ECS Fargate, keep costs minimal."

The skill will:

  1. Research Fargate Spot pricing, right-sizing strategies, and ALB vs API Gateway trade-offs.
  2. Generate Terraform modules for VPC, ECS cluster, Fargate service, ALB, and ECR repository.
  3. Configure auto-scaling based on CPU utilization with conservative thresholds for cost optimization.
  4. Produce a cost estimate comparing Fargate vs Fargate Spot for the expected workload.
Example 3: Kubernetes on Azure AKS

User: "Set up a production AKS cluster with monitoring and RBAC."

The skill will:

  1. Research AKS best practices for node pool sizing, network policies, and Azure AD integration.
  2. Generate Terraform for the AKS cluster, node pools, Azure Monitor workspace, and RBAC role assignments.
  3. Create Kubernetes manifests for ingress controller, cert-manager, and Prometheus stack.
  4. Include a runbook covering cluster upgrades, node pool scaling, and incident response.

Error Handling

  • Unknown platform: Prompts the user to specify a supported cloud provider or platform.
  • Insufficient context: Asks clarifying questions about the application type, expected traffic, and budget before generating configs.
  • Web search unavailable: Falls back to built-in knowledge of common deployment patterns, noting that the recommendations may not reflect the latest documentation.
  • Conflicting requirements: Identifies trade-offs (e.g., "HIPAA compliance requires dedicated tenancy which increases costs beyond the $50 budget") and asks the user to prioritize.

Prerequisites

  • Target cloud provider CLI authenticated (gcloud, aws, or az)
  • Terraform >= 1.5 installed (for IaC output)
  • Docker installed (for container-based deployments)
  • WebSearch and WebFetch tools enabled for best-practice research

Resources

© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/.curated/research-to-deploy of jeremylongshore/tons-of-skills-marketplace.

Open the folder on GitHubat commit cfae287

Compare with similar skills

Research To Deploy next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Research To Deploy compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Research To Deploy this skilljeremylongshore/tons-of-skills-marketplace2.8k—~1.8kAutomated safety check: PassMIT
Senior DevOps Toolkitmaslennikov-ig/claude-code-orchestrator-kit2606 repos~1.1kAutomated safety check: NotesCustom licence
Discover Infrarand/cc-polymath181—~783Automated safety check: PassMIT
Agent Bom Scan InfraLeoYeAI/openclaw-master-skills2.2k—~1.5kAutomated safety check: PassApache-2.0
DeployingGoogleCloudPlatform/race-condition234—~3kAutomated safety check: PassCustom licence
Supercheck Infrastructure Deploymentsupercheck-io/supercheck215—~1.4kAutomated safety check: NotesAGPL-3.0

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Works with

Categories

Questions about Research To Deploy

What does Research To Deploy do?

Researches infrastructure best practices and generates deployment-ready configurations, Terraform modules, Dockerfiles, and CI/CD pipelines. Research To Deploy is an agent skill from jeremylongshore/tons-of-skills-marketplace. Researches infrastructure best practices and generates deployment-ready configurations, Terraform modules, Dockerfiles, and CI/CD pipelines.

When should I use Research To Deploy?

Research To Deploy fits situations like: the user needs to deploy services; set up infrastructure; create cloud configurations based on current best practices; with phrases like research and deploy.

How do I install Research To Deploy in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill research-to-deploy -a claude-code`. Or copy the skill folder (skills/.curated/research-to-deploy in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/research-to-deploy in your project. Claude Code loads it when a task matches its description.

How do I install Research To Deploy in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill research-to-deploy -a codex`. Or copy the skill folder (skills/.curated/research-to-deploy in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/research-to-deploy in your project. Codex loads it when a task matches its description.

Can I use Research To Deploy in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill research-to-deploy -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/research-to-deploy, .gemini/skills/research-to-deploy, .github/skills/research-to-deploy and .opencode/skills/research-to-deploy in your project.

What does Research To Deploy need to run?

Going by SKILL.md and its folder, Research To Deploy needs the command-line tools its instructions call (terraform, docker and kubectl). Our summary lists: Python 3; Node.js; Docker. Its frontmatter pre-approves these tools: Read, Write, Edit, Bash(terraform:*), Bash(docker:*), Bash(kubectl:*), Bash(git:*), Bash(npm:*), Glob, Grep, WebSearch, WebFetch. Compatibility (from SKILL.md): Designed for Claude Code.

Does Research To Deploy access the network?

SKILL.md names 3 domains. As links in the text: registry.terraform.io, aws.amazon.com and cloud.google.com. This is read from the text; nothing was executed.

Is Research To Deploy safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Research To Deploy use?

Research To Deploy is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Research To Deploy use?

About 1.8k tokens (SKILL.md is roughly 7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Research To Deploy?

Skills that share tags, products or a category with Research To Deploy: Senior DevOps Toolkit (maslennikov-ig/claude-code-orchestrator-kit, 260 stars), Discover Infra (rand/cc-polymath, 181 stars), Agent Bom Scan Infra (LeoYeAI/openclaw-master-skills, 2.2k stars) and Deploying (GoogleCloudPlatform/race-condition, 234 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Research To Deploy?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.

Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.