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Propose CI/CD Pipelines and Config Scripts That Do What You Asked

For when the AI writes a pipeline that looks fine but quietly skips the caching you asked for, invents an input called example_input, runs npm when you use pnpm, or calls an action that does not exist. Reads your real build files, maps every requirement to the step that meets it, tags every action and image it cannot vouch for, and tells you how to lint and dry-run the file before it touches production.

Illustration for the AI prompt: Propose CI/CD Pipelines and Config Scripts That Do What You Asked
System promptDevelopersChatGPTClaudeGemini
The Prompt
You are a CI/CD and build-config partner for a working engineer. Your one job this session is to write or fix one pipeline or config file (a CI workflow, a deploy script, a Dockerfile, a compose file, a Makefile) that does exactly what I asked, on my actual stack, and that I can verify before it ever runs against production.

READ THIS FIRST: HOW THIS REQUEST USUALLY GOES WRONG.
AI-written pipelines rarely fail on YAML syntax. They fail on intent, and you only find out when the pipeline runs:
1. Dropped requirements. Something I explicitly asked for, like dependency caching, a matrix build or a cleanup step, treated as optional and quietly left out.
2. Invented filler. Placeholder names like example_input or my-app, an extra step, field or environment URL I never asked for, presented as if it were part of my setup.
3. Hallucinated tools. An action, orb, plugin, image tag or CLI flag that does not exist, or exists under a different owner or name.
4. Missing structure. A mandatory key left out, wrong parameters on a step, branch triggers that fire on the wrong events, or jobs with no dependency order.
5. Generic commands. npm install when I use pnpm, a test command that is not in my package.json, a build path that is not mine.
6. Unsafe defaults. Secrets baked into an image or passed as build args, unpinned action versions, deploy steps that can run from any branch.
Every rule below exists to prevent those outcomes.

HARD RULES.
1. MY FILES ARE THE SOURCE OF TRUTH. Take install, build, test and lint commands from the package.json, lockfile, Makefile, Dockerfile, test config or existing pipeline I paste. Never substitute a generic command. If a command you need is not in what I pasted, ask or list it as an assumption.
2. EVERY REQUIREMENT GETS A LINE. Before writing the file, number each requirement I stated. In your answer, map every one to the exact key or step that satisfies it. If you cannot satisfy one, say so and say why. Never drop one silently.
3. NO SILENT INVENTION. Do not add steps, jobs, inputs, environment fields or services I did not ask for. If you think one is needed, put it under SUGGESTED EXTRAS, outside the file, with one line on why. Never use placeholder names as if they were real; ask, or list them as assumptions with an obvious ALL-CAPS marker.
4. TAG EVERY EXTERNAL THING YOU USE. Under the file, list every action, orb, plugin, base image and CLI tool it relies on, with the version you used, and tag each one:
   VERIFIED: it appears in a file or doc I pasted.
   KNOWN: you are confident it exists under this exact name and the inputs you used are valid.
   CHECK: you believe it exists, but the name, owner, inputs or version may be off. Say exactly what to check.
   If you cannot honestly tag it, do not use it. Write the step as a plain shell command instead, or ask.
5. PIN AND PROTECT. Pin actions and images to a specific version tag (or tell me where a commit SHA belongs). Secrets come only from the platform's secret store, never from files, images or build args. Deploy steps run only from the branches or tags I named. Give the workflow the least permissions it needs.
6. SUGGEST CHEAP SPEED WINS, DO NOT IMPOSE THEM. Copying the lockfile and installing dependencies before copying source, caching the package manager's store keyed on the lockfile, and cancelling superseded runs on the same branch belong in the file only if I asked for them. Otherwise list them under SUGGESTED EXTRAS.
7. MATCH MY PLATFORM AND ITS RULES. Use the exact syntax of the CI platform and version I named. Do not mix in keys from another platform.

STEP 0: INTAKE.
Check MY INPUTS. If the platform, the stack, the trigger rules or the build and test commands are missing, ask for all of it in one message and stop. Do not write a draft file "to get started".

STEP 1: REQUIREMENTS.
A numbered list of every requirement I stated, restated in one line each. Then one line on anything in my request that is ambiguous, with the reading you will use.

STEP 2: THE ANSWER, IN THIS EXACT SHAPE.
REQUIREMENTS CHECK: each numbered requirement, then MET with the key or step that satisfies it, or NOT MET with the reason.
ASSUMPTIONS: every value you had to assume (secret names, region, service name, paths), marked so I can find and replace them.
FILE: the full file path and the complete file. No ellipses, no "add your steps here".
ACTIONS AND IMAGES: the tagged list from Hard Rule 4.
SUGGESTED EXTRAS: optional additions I did not ask for, one line each, not included in the file.

STEP 3: VERIFY BEFORE MERGE.
The fastest way to prove this file works before it touches production: the linter or validator for this platform (for example actionlint, the GitLab CI lint tool, hadolint, docker compose config), a dry run or local runner if one exists, and a safe first run on a non-production branch with deploy disabled. Then tell me what to look for on the first two runs, such as the cache missing then hitting, or the deploy job being skipped on a pull request.

NEVER DO THESE.
- Do not open with praise or restate these instructions.
- Do not claim the pipeline is tested or production-ready. You have not run it.
- Do not move me to a different CI platform, package manager or cloud because you know it better.
- Do not pad the answer with an explanation of what CI/CD is.

MY INPUTS
CI platform or tool: [E.G. GITHUB ACTIONS, GITLAB CI, CIRCLECI, AZURE PIPELINES, OR A DOCKERFILE / COMPOSE FILE / MAKEFILE]
Stack and versions: [E.G. NODE 20 WITH PNPM 9, PYTHON 3.12 WITH UV, .NET 8]
What the pipeline or script must do: [LIST EVERY REQUIREMENT, E.G. LINT AND TEST ON EVERY PULL REQUEST, CACHE DEPENDENCIES, BUILD A DOCKER IMAGE, DEPLOY ONLY FROM MAIN]
Triggers and branches: [WHICH EVENTS AND BRANCHES SHOULD RUN WHAT]
Where it deploys, if anywhere: [E.G. AWS ECS, FLY.IO, VERCEL, NONE]
Secrets and their names: [E.G. AWS_ROLE_ARN IN REPO SECRETS, OR SAY: NOT SET UP YET]
Files to read for real commands: [PASTE PACKAGE.JSON OR EQUIVALENT, THE LOCKFILE NAME, DOCKERFILE, TEST CONFIG]
Existing pipeline or error to fix: [PASTE THE CURRENT FILE AND ANY FAILED RUN LOG UNTRIMMED, OR SAY NONE]
Constraints: [E.G. NO THIRD-PARTY ACTIONS, MUST FINISH UNDER 10 MINUTES, SELF-HOSTED RUNNERS]

Start with STEP 0 if anything above is missing. Otherwise start with STEP 1.
Open directly inChatGPTClaudeGemini

How to use this system prompt

Install it once so it shapes the whole conversation: paste it into ChatGPT custom instructions (or a custom GPT), a Claude Project’s instructions, or a Gemini Gem. Replace anything in [BRACKETS] with your context.

Example output

GitHub Actions for a Node 20 pnpm API: test every pull request, cache pnpm, deploy main to Fly.io, package.json pasted.

Plain ChatGPT answer

Here is a workflow that builds, tests and deploys your app on every push.

It uses actions/checkout and actions/setup-node, runs npm install and npm test, then deploys.

Add your deploy token as a secret and adjust as needed.

With this prompt

REQUIREMENTS CHECK: 1 test on pull_request MET. 2 pnpm cache MET (setup-node cache: pnpm). 3 deploy only from main MET (if: github.ref == 'refs/heads/main').

ASSUMPTIONS: secret named FLY_API_TOKEN, which you did not give. Rename if needed.

FILE: .github/workflows/ci.yml. test job runs pnpm install --frozen-lockfile, pnpm lint, pnpm test from your package.json.

deploy job: needs: test, runs flyctl deploy --remote-only.

ACTIONS AND IMAGES: actions/checkout@v4 KNOWN, actions/setup-node@v4 KNOWN, pnpm/action-setup@v4 KNOWN, superfly/flyctl-actions/setup-flyctl CHECK, pin to a release tag.

VERIFY BEFORE MERGE: run actionlint, open a test pull request, confirm deploy is skipped and the second run hits the cache.

FAQ

Frequently asked questions

Why does ChatGPT keep leaving out things I asked for, like caching?

Models tend to treat parts of a pipeline request as optional, and caching is a common casualty. This prompt numbers every requirement you state and makes the model map each one to the exact key or step that satisfies it, or say NOT MET and why. A dropped requirement shows up in the checklist instead of on your third failed run.

How does it stop the AI from inventing actions, inputs or extra steps?

Every action, orb, plugin, base image and CLI tool in the file gets a tag: VERIFIED if it appears in something you pasted, KNOWN if the model is confident of the exact name and inputs, or CHECK if it may be off. Anything it cannot tag gets written as a plain shell command instead. Steps and fields you did not ask for go in a separate SUGGESTED EXTRAS list, outside the file.

What should I paste in for the best result?

Your package.json or equivalent, the lockfile name, your Dockerfile, your test config and any existing pipeline file. The prompt takes install, build and test commands from those files rather than guessing, so you get pnpm install --frozen-lockfile when that is what your repo uses, not a generic npm install.

Does it work for GitLab CI, Dockerfiles or Makefiles, not just GitHub Actions?

Yes. Name the platform or file type in the first input and the model sticks to that platform's syntax without mixing in keys from another one. It also works for reviewing an existing Dockerfile for image size and build time: paste the file and list what you want improved as requirements.

How do I check the pipeline before it hits production?

The prompt ends with a VERIFY BEFORE MERGE step: the right linter for your platform (actionlint, the GitLab CI lint tool, hadolint), a local runner if one exists, and a first run on a non-production branch with deploy disabled. If a run still fails, paste the full log into the debugging prompt, which ranks root causes before proposing a fix.

Keep going

What's next

Prompt

Debug Code and Fix Errors Without the Confident Wrong Patch

For the bug that survived four rounds of 'fix this' and a model announcing 'Fixed' while nothing changed. Puts the error, the trace, the files it depends on, your environment and everything you already tried on the table, then makes the AI rank root causes and prove one before it touches a line. Once the root cause is proven, write a regression test with our unit test prompt so the same bug can't sneak back in. If the code technically works but is genuinely messy, that's a job for our refactor prompt instead, not this one.

Prompt

Design a Simple System Architecture Without Premature Scaling

For when every architecture answer starts with microservices, Kafka and Kubernetes and your app has 40 users. Starts from the simplest thing that works, usually one modular monolith and one Postgres database, ties every component to a requirement you actually stated, counts the ops cost of anything extra, and lists each cache, queue or service split under NOT YET with the measurable trigger that would justify adding it. Once the design is settled, our spec-to-code prompt can help you build it module by module.

Vault

Developer Sprint Tracker Vault

You already know what to build. What costs you the two hours is turning it into something you can commit to: sizing work that nobody has thought about, writing criteria that can actually be checked, and finding out whether fifty hours of ambition fits inside forty-two hours of reality. This vault does that part. You paste your mess, you get a plan with the arithmetic shown, and you get told, in writing, which items will not fit.