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Containerization Assistant Skill · a5c-ai | DecimalAI

a5c-ai/containerization-assistant

SkillScore44Maintained

Assist in containerizing applications with Dockerfile generation and optimization

DevOpsby a5c-ai

Links this skill to your agents and keeps it current with the author’s updates.

Automatic

DevOps & SRE pack

1 · One-time — install the CLI (docs ↗)

pip install decimalai

2 · Get the skill — writes .claude/skills/a5c-ai-containerization-assistant/SKILL.md

decimalai skills pull a5c-ai-containerization-assistant --out .claude/skills/

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/a5c-ai-containerization-assistant/SKILL.md https://app.decimal.ai/s/a5c-ai-containerization-assistant/SKILL.md

Raw file: /s/a5c-ai-containerization-assistant/SKILL.md ↗ · machine-readable summary at /s/a5c-ai-containerization-assistant.json ↗

In productionGlobal

how this skill behaves on real traffic · last 30 days

No production data for this skill yet — usage numbers appear here once agents start running it.

Anonymized aggregate across every org using this skill — proof from real production use, not a demo.

Does this skill help? · Benchmark: with vs. withoutsign in to run this on your agents

25 test cases from the publisher’s eval.yaml · each run twice on gemini-3.6-flash — with the skill injected, then without · last run 58d ago

Yes — +40% lift+8% tokens0% turns44% of whole cases pass with skill (11/25)

Test case	Without → With	Effect	Δ tokens	Δ turns
case-01	✗→✓	▲ Improved	6%	0%
case-02	✗→✓	▲ Improved	-34%	0%
case-03	✗→✓	▲ Improved	-5%	0%
case-14	✗→✓	▲ Improved	6%	0%
case-15	✗→✓	▲ Improved	-27%	0%

Showing 5 of 25 cases

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 7/31/2026

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

a5c-ai / babysitter

library/specializations/code-migration-modernization/skills/containerization-assistant/SKILL.md

View on GitHub ↗

License MITImported 7/31/2026Version v1

Skill contents

SKILL.md

Containerization Assistant Skill

Assists in containerizing applications by generating Dockerfiles, optimizing images, and configuring container deployments.

Purpose

Enable application containerization for:

Dockerfile generation
Multi-stage build optimization
Base image selection
Dependency packaging
Security scanning

Capabilities

1. Dockerfile Generation

Generate from application analysis
Support multiple languages
Include best practices
Handle build dependencies

2. Multi-Stage Build Optimization

Separate build and runtime
Minimize image size
Cache build layers
Optimize build time

3. Base Image Selection

Recommend appropriate base images
Balance size vs features
Consider security updates
Handle distroless options

4. Dependency Packaging

Bundle application dependencies
Handle native extensions
Configure build tools
Manage versions

5. Health Check Configuration

Add health checks
Configure readiness probes
Set up liveness probes
Define startup probes

6. Security Scanning

Scan for vulnerabilities
Check base image security
Identify exposed secrets
Review permissions

Tool Integrations

| Tool | Purpose | Integration Method | |------|---------|-------------------| | Docker | Container runtime | CLI | | Buildpacks | Auto-detection | CLI | | Jib | Java containers | CLI | | ko | Go containers | CLI | | Dive | Image analysis | CLI | | Trivy | Security scanning | CLI |

Output Schema

json
{
  "containerizationId": "string",
  "timestamp": "ISO8601",
  "application": {
    "name": "string",
    "language": "string",
    "framework": "string"
  },
  "artifacts": {
    "dockerfile": "string",
    "dockerignore": "string",
    "composeFile": "string"
  },
  "image": {
    "baseImage": "string",
    "estimatedSize": "string",
    "stages": "number"
  },
  "security": {
    "vulnerabilities": [],
    "recommendations": []
  }
}

Integration with Migration Processes

containerization: Primary containerization tool
cloud-migration: Container deployment
monolith-to-microservices: Service extraction

Related Skills

iac-generator: Kubernetes IaC
cloud-readiness-assessor: Container readiness

Related Agents

cloud-migration-engineer: Container deployment
infrastructure-migration-agent: Container infrastructure

Illustrative Want to see what a5c-ai/containerization-assistant would put in front of your model? Preview the rendered body and check its trigger phrases — no LLM call, no signup.

Latest benchmark · publisher runVerified

8/1/2026, 01:36 UTC · 25 cases

Lift

+40%

44% vs 4%

Agent turns

0%

1.0 vs 1.0

Tokens

+8%

1,914.72 vs 1,780.84

fail → pass · 10pass → pass · 1fail → fail · 14

Per-case results (25)

Case	Status	Duration (ms)			Turns			Tokens			Tool calls
Case	Status	Without	With	Δ	Without	With	Δ	Without	With	Δ	Without	With	Δ
case-01 I need to containerize my Node.js Express web application named 'payment-service'. Could you analyze the setup and generate the necessary deployment files? Please provide a response formatted as JSON that includes a containerizationId, timestamp, application details (name, language, framework), generated artifacts (dockerfile, dockerignore, composeFile), image specs (base image, estimated size, stage count), and security scan results with recommendations.	fail→pass	11,675	9,387	-20%	1	1	0%	2,654	2,818	+6%	0	0	—
case-02 We are preparing to package a Python FastAPI service called 'inventory-api' into containers. Please run a full containerization process and produce the output as a JSON object containing application info, generated Dockerfile and Compose artifacts, estimated image size and base image details, along with any security vulnerabilities and recommendations found.	fail→pass	21,515	10,560	-51%	1	1	0%	4,386	2,905	-34%	0	0	—
case-03 Please create an optimized container build configuration for a Java Spring Boot microservice called 'order-processor'. Return the final result in JSON format with fields for containerizationId, application metadata, artifact contents (dockerfile, dockerignore, composeFile), image build statistics (base image, size estimate, stages), and security evaluation findings.	fail→pass	14,983	13,042	-13%	1	1	0%	3,535	3,349	-5%	0	0	—
case-04 We are packaging a Java Spring Boot application into a Docker container. We want to build container images directly from our Maven build process without requiring a running Docker daemon installed on the build server. Which build tool integration should be used for this Java workflow, and what CLI tool handles it?	fail→fail	5,829	7,013	+20%	1	1	0%	1,086	1,957	+80%	0	0	—
case-05 We have a Go web microservice and want to generate small, secure OCI images without writing or maintaining a Dockerfile manually. Which tool integration is designated for Go applications?	fail→fail	9,622	4,881	-49%	1	1	0%	1,434	1,351	-6%	0	0	—
case-06 Our team wants to inspect the layer-by-layer contents and wasted space efficiency of an existing Docker image from the command line. Which tool integration in the containerization toolchain provides image layer analysis?	fail→fail	7,225	2,945	-59%	1	1	0%	1,121	1,071	-4%	0	0	—
case-07 We need to perform CLI-based security scanning on our built container images to detect OS package vulnerabilities and exposed secrets before pushing to our registry. Which tool integration handles container security scanning?	fail→fail	8,846	3,189	-64%	1	1	0%	1,714	1,168	-32%	0	0	—
case-08 We have a polyglot repository and want to automatically detect language runtimes and build container images without creating explicit Dockerfiles. Which CLI tool integration handles auto-detection container builds?	fail→fail	8,301	4,444	-46%	1	1	0%	1,568	1,438	-8%	0	0	—
case-09 We are choosing a base image for a production Python FastAPI service that depends on binary C extensions like NumPy and asyncpg. We are considering Alpine Linux versus Debian Slim. Which base image option should be selected to avoid C extension compilation failures?	fail→fail	10,402	10,725	+3%	1	1	0%	2,034	2,870	+41%	0	0	—
case-10 We are writing a Dockerfile for a Go microservice binary. In the build stage we compile using the official Go image. For the final runtime stage, we want to eliminate shell vulnerabilities and minimize image size. What base image choice should be used for the runtime stage?	fail→fail	9,576	10,149	+6%	1	1	0%	1,896	2,186	+15%	0	0	—
case-11 We need to configure container health monitoring in a Dockerfile for a web microservice running on port 8080 at path `/health`. What instruction should be added to the Dockerfile to check endpoint status?	fail→fail	4,140	5,229	+26%	1	1	0%	905	1,682	+86%	0	0	—
case-12 In our Node.js Dockerfile, `npm install` runs on every code change because source files are copied before dependency files. How should file copying instructions be ordered to leverage layer caching?	fail→fail	6,625	6,620	-0%	1	1	0%	1,387	1,895	+37%	0	0	—
case-13 By default, Docker containers run as the root user, creating a security risk in production environments. What instruction should be added to the Dockerfile to change the runtime user context?	fail→fail	3,676	4,498	+22%	1	1	0%	562	1,458	+159%	0	0	—
case-14 Generate a containerization response for a Python FastAPI app named 'analytics-worker' using standard JSON schema format. How should application metadata be structured in the output?	fail→pass	12,568	9,472	-25%	1	1	0%	2,196	2,334	+6%	0	0	—
case-15 When returning generated containerization files for a Ruby on Rails application named 'storefront', what properties should be placed under the `artifacts` key in the response JSON?	fail→pass	11,206	4,021	-64%	1	1	0%	1,875	1,375	-27%	0	0	—
case-16 We are containerizing a Single Page App built with React that compiles static assets with Node and serves them via Nginx. How many stages should be declared in the schema's `image.stages` property?	pass→pass	6,163	5,552	-10%	1	1	0%	873	1,445	+66%	0	0	—
case-17 We ran a vulnerability audit on a legacy application image. In the standardized output schema, how should security scan results be organized to separate identified flaws from remediation steps?	fail→pass	15,521	10,856	-30%	1	1	0%	2,475	2,498	+1%	0	0	—
case-18 We have finished containerizing our application and now need Kubernetes manifests for deployment, services, and ingress. Which related skill in the migration ecosystem generates infrastructure-as-code manifests?	fail→pass	9,148	3,620	-60%	1	1	0%	1,515	1,142	-25%	0	0	—
case-19 Before starting containerization, we need to evaluate whether an existing monolithic enterprise application is ready for container deployment. Which related skill conducts this cloud readiness assessment?	fail→pass	7,674	3,160	-59%	1	1	0%	1,062	963	-9%	0	0	—
case-20 During a cloud migration program, which specialized agent role is responsible for executing container deployments to cloud environments?	fail→pass	5,448	2,272	-58%	1	1	0%	935	878	-6%	0	0	—
case-21 Which specialized agent role handles container infrastructure provisioning and cloud setup during infrastructure migrations?	fail→pass	8,321	2,114	-75%	1	1	0%	1,105	904	-18%	0	0	—
case-22 We are configuring ignore rules for Docker image builds of a Node.js application to keep image sizes small and protect credentials. Which build artifact directory should be excluded in the `.dockerignore` file?	fail→fail	7,538	8,666	+15%	1	1	0%	1,038	1,684	+62%	0	0	—
case-23 Our Kubernetes cluster running in AWS EKS needs autoscaling configured. We want nodes to scale out when CPU utilization across the node group exceeds 75% for 5 minutes. Should we configure Horizontal Pod Autoscaler or Cluster Autoscaler for adding EC2 worker instances, and how should node groups be defined?	fail→fail	17,764	16,852	-5%	1	1	0%	2,690	3,655	+36%	0	0	—
case-24 We need to set up a GitHub Actions workflow that triggers on pull requests to run our unit tests, linter, and integration tests for a Rust service. How should we write the `.github/workflows/ci.yml` file to cache cargo dependencies and run cargo test?	fail→fail	11,269	10,315	-8%	1	1	0%	1,973	2,552	+29%	0	0	—
case-25 We are deploying an existing container image to Kubernetes using Helm. Can you write a `values.yaml` file and ingress template specifying TLS secrets and cert-manager annotations for our hostname api.example.com?	fail→fail	11,385	7,982	-30%	1	1	0%	2,502	2,290	-8%	0	0	—

These cases were also screened by the skill’s intent / safety pass.See the Trust review ↗Reproduce this benchmark in Colab ↗

How this skill was measured

DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 25 cases were attempted. The headline lift of +40 percentage points is the difference between those two pass rates over the 25 comparable cases.

Model measured: gemini-3.6-flash
Graded by: gemini-3.6-flash
Grading method: judged
Verification: verified
Pass rate without the skill: 4%
Pass rate with the skill: 44%
Cases attempted: 25
Cases counted toward lift: 25
Cases that regressed: 0
Skill version measured: v1
Run completed: 8/1/2026, 01:36 UTC

Measured example — same prompt, with vs. without the skill · from the benchmark run · case case-01

Prompt

I need to containerize my Node.js Express web application named 'payment-service'. Could you analyze the setup and generate the necessary deployment files? Please provide a response formatted as JSON that includes a containerizationId, timestamp, application details (name, language, framework), generated artifacts (dockerfile, dockerignore, composeFile), image specs (base image, estimated size, stage count), and security scan results with recommendations.

Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.

Show both answers

SkillScore blends 4 signals1 of 4 complete

BenchmarkPass rate WITH skill on a verified run44

Live evalNeeds ≥10 evaluated traces in 30 days

AI ratingNeeds ≥10 rated traces

AdoptionNeeds ≥10 serves across ≥2 orgs in 30 days

Efficiency · separate axis (at equal correctness)+0% turns+66% tokens

Shown for transparency; not credited unless a verified run shows no correctness regression.

Backed by 1 of 4 signals — each added signal makes the score more robust.

Verified on gemini-3.6-flash · re-tested 57 days ago

Other measured skills in the registry, with their headline benchmark lift.