Build correctness
Ask for base image choice, lockfile handling, dependency install order, build artifacts, environment variables, and reproducible build checks.
🤖 Interactive Dockerfile review builder
Dockerfile Review Prompt Generator
By Omellody Editorial Team · Published · UpdatedUse this existing Omellody prompt utility to review a Dockerfile for image size, layer caching, dependency pinning, build secrets, non-root runtime, health checks, and deployment safety. The builder runs locally in your browser and does not submit project details to Omellody.
Interactive prompt builder
Replace the examples with sanitized project details. The generated prompt updates locally in the browser.
{context}{stack}{goal}{constraints}
Act as a senior software engineer, technical writer, and careful reviewer. Help me create a Dockerfile review from the real context below.
Project context: {context}
Stack or tools: {stack}
Goal: {goal}
Constraints: {constraints}
Return these sections:
1. Direct recommendation with assumptions called out.
2. Decision table: hypothesis or option, evidence needed, risk, and next action.
3. Step-by-step plan with safe first checks before any destructive change.
4. Security, privacy, reliability, and maintainability review.
5. Tests or verification steps before merge, deploy, or publication.
6. Rollback, escalation, or reviewer handoff plan if the recommendation is wrong.
7. Final implementation checklist.
Rules: do not invent production facts, credentials, private URLs, secrets, customer data, undocumented behavior, or hidden requirements. If information is missing, write “assumption” or “needs confirmation” instead of guessing.
Copy-ready base prompt
Act as a senior software engineer, technical writer, and careful reviewer. Help me create a Dockerfile review from the real context below.
Project context: {context}
Stack or tools: {stack}
Goal: {goal}
Constraints: {constraints}
Return these sections:
1. Direct recommendation with assumptions called out.
2. Decision table: hypothesis or option, evidence needed, risk, and next action.
3. Step-by-step plan with safe first checks before any destructive change.
4. Security, privacy, reliability, and maintainability review.
5. Tests or verification steps before merge, deploy, or publication.
6. Rollback, escalation, or reviewer handoff plan if the recommendation is wrong.
7. Final implementation checklist.
Rules: do not invent production facts, credentials, private URLs, secrets, customer data, undocumented behavior, or hidden requirements. If information is missing, write “assumption” or “needs confirmation” instead of guessing.
Prompt formula and variables
Formula: Runtime goal + current Dockerfile shape + package manager + deployment target + security constraints + build-speed target.
| Variable | What to enter |
|---|---|
{context} | Project context: add specific, safe, non-confidential details from the real project. |
{stack} | Stack or tools: add specific, safe, non-confidential details from the real project. |
{goal} | Goal: add specific, safe, non-confidential details from the real project. |
{constraints} | Constraints: add specific, safe, non-confidential details from the real project. |
Security hardening
Require review for secrets in layers, non-root user, minimal packages, pinned versions, vulnerability scanning, and writable filesystem assumptions.
Deployability
Include health checks, signal handling, startup commands, migration separation, image tags, rollback notes, and CI cache strategy.
Output review table
| Check | Pass condition | Fix if weak |
|---|---|---|
| Specificity | The answer references your actual stack, workflow, constraints, and risk tolerance. | Add concrete versions, tools, traffic assumptions, data boundaries, or deployment rules. |
| Security | No secrets are exposed and auth, permissions, data privacy, logging, and abuse risks are reviewed. | Ask for a dedicated security pass and remove sensitive details before using public AI tools. |
| Maintainability | The output explains tradeoffs, owner handoffs, monitoring, rollback, and future maintenance. | Request an ADR-style decision record, docs owner, or implementation checklist. |
| Verification | The answer includes tests, manual checks, source-of-truth references, and production-readiness gates. | Ask for test cases, staging checks, failure cases, and observability signals. |
Source snapshot
| Item | Snapshot |
|---|---|
| Page type | Existing Omellody coding prompt utility page; refreshed in Red Mode for depth, original utility, and internal discovery. |
| Demand signal | URL inventory on 2026-05-22 flagged this coding prompt family as thin with low internal-link depth; traffic radar continues to show AI prompt generator demand. |
| Originality | Omellody-created prompt, formula, variable model, review table, FAQ, source snapshot, and browser-side builder. No external repository content copied. |
| Last reviewed | 2026-05-22 |
FAQ quick table
| Question | Short answer |
|---|---|
| What should a Dockerfile review prompt include? | Include the Dockerfile, package manager, runtime, deployment target, current pain points, security constraints, and desired output format. |
| Should I paste my whole Dockerfile? | You can paste sanitized Dockerfile content, but remove tokens, private registry names, internal paths, and customer or proprietary details. |
| What are common Dockerfile review issues? | Common issues include secrets in layers, missing lockfiles, root runtime, oversized images, poor caching, unpinned dependencies, and unsafe entrypoints. |
Related coding prompt tools
FAQ
What should a Dockerfile review prompt include?
Include the Dockerfile, package manager, runtime, deployment target, current pain points, security constraints, and desired output format.
Should I paste my whole Dockerfile?
You can paste sanitized Dockerfile content, but remove tokens, private registry names, internal paths, and customer or proprietary details.
What are common Dockerfile review issues?
Common issues include secrets in layers, missing lockfiles, root runtime, oversized images, poor caching, unpinned dependencies, and unsafe entrypoints.
Can AI replace container security scanning?
No. Use AI for review structure, then run actual scanners, tests, and deployment checks in your pipeline.