Fingerprint CI Gate
liarjsdev/liarjs-skills
Gate a build on browser fingerprint regressions with liarjs - save a baseline scan as JSON, diff later runs against it, and fail the job when the consistency score falls below a floor.
Set up a continuous integration and continuous delivery (CI/CD) pipeline for a software project, automating builds, tests, and deployments across environments.
$ npx skills add seb1n/awesome-ai-agent-skills --skill ci-cd -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install seb1n/awesome-ai-agent-skills ci-cd --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/devops-and-infrastructure/ci-cd .claude/skills/ci-cd && rm -rf skills-srcUse ~/.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/
Install the "ci-cd" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/devops-and-infrastructure/ci-cd into .claude/skills/ci-cd/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ci-cd", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/seb1n/awesome-ai-agent-skills/tree/main/devops-and-infrastructure/ci-cdType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add seb1n/awesome-ai-agent-skills --skill ci-cd -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install seb1n/awesome-ai-agent-skills ci-cd --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/devops-and-infrastructure/ci-cd .agents/skills/ci-cd && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ci-cd" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/devops-and-infrastructure/ci-cd into .agents/skills/ci-cd/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ci-cd", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add seb1n/awesome-ai-agent-skills --skill ci-cd -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install seb1n/awesome-ai-agent-skills ci-cd --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/devops-and-infrastructure/ci-cd .cursor/skills/ci-cd && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "ci-cd" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/devops-and-infrastructure/ci-cd into .cursor/skills/ci-cd/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ci-cd", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/seb1n/awesome-ai-agent-skills.git --path devops-and-infrastructure/ci-cd--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add seb1n/awesome-ai-agent-skills --skill ci-cd -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install seb1n/awesome-ai-agent-skills ci-cd --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/devops-and-infrastructure/ci-cd .gemini/skills/ci-cd && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "ci-cd" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/devops-and-infrastructure/ci-cd into .gemini/skills/ci-cd/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ci-cd", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install seb1n/awesome-ai-agent-skills ci-cdInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add seb1n/awesome-ai-agent-skills --skill ci-cd -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/devops-and-infrastructure/ci-cd .github/skills/ci-cd && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "ci-cd" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/devops-and-infrastructure/ci-cd into .github/skills/ci-cd/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ci-cd", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add seb1n/awesome-ai-agent-skills --skill ci-cd -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install seb1n/awesome-ai-agent-skills ci-cd --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/devops-and-infrastructure/ci-cd .opencode/skills/ci-cd && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "ci-cd" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/devops-and-infrastructure/ci-cd into .opencode/skills/ci-cd/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ci-cd", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
ci-cdSet up a continuous integration and continuous delivery (CI/CD) pipeline for a software project, automating builds, tests, and deployments across environments.
CI CD is an agent skill from seb1n/awesome-ai-agent-skills. Set up a continuous integration and continuous delivery (CI/CD) pipeline for a software project, automating builds, tests, and deployments across environments. Use when the user requests ci cd or provides relevant inputs for this workflow.
Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in DevOps & Cloud, covering CI/CD. It works with GitLab. The repository describes itself as: 103 ready-to-use AI agent skills for Claude Code, OpenAI Codex, Gemini CLI, Cursor, GitHub Copilot, Windsurf, and other Agent Skills-compatible tools. Complete SKILL.md… The licence is MIT.
6 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 75865a5. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are yaml).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
POSTGRES_PASSWORDAWS_ACCESS_KEY_IDAWS_SECRET_ACCESS_KEYGITHUB_TOKENCI_REGISTRY_PASSWORDSSH_PRIVATE_KEYFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
CI CD loads about 2.9k tokens when it runs. Until then it costs about 61 tokens; SKILL.md has 791 words of instructions outside code blocks.
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.
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.
The full file from seb1n/awesome-ai-agent-skills at commit 75865a5, republished under its MIT licence (© seb1n). 791 words, ~2,894 tokens.
.claude/skills/ci-cd/SKILL.md (or your agent's skills folder).This skill enables the agent to design, configure, and maintain CI/CD pipelines that automate the entire software delivery lifecycle. The agent can set up pipeline stages including linting, testing, building, deploying, and notifying stakeholders, ensuring that every code change is validated and delivered reliably. The agent understands secrets management, caching strategies, matrix builds, and deployment strategies such as blue/green and canary releases.
Assess the Project and Choose a Platform: The agent analyzes the project's language, framework, hosting environment, and team preferences to recommend a CI/CD platform. Options include GitHub Actions, GitLab CI/CD, Jenkins, CircleCI, and Azure DevOps. The agent considers factors like repository hosting, cost, plugin ecosystem, and integration with existing tools before making a recommendation.
Define Pipeline Stages: The agent structures the pipeline into discrete stages: lint (static analysis and code style), test (unit, integration, and end-to-end), build (compilation, bundling, Docker image creation), deploy (staging and production), and notify (Slack, email, or webhook alerts). Each stage has clearly defined inputs, outputs, and failure conditions so the pipeline fails fast on errors.
Configure Secrets and Environment Variables: The agent sets up secure storage for API keys, database credentials, cloud provider tokens, and other sensitive values using the platform's native secrets manager (e.g., GitHub Secrets, GitLab CI/CD Variables, or Jenkins Credentials). Secrets are never hardcoded in pipeline files and are scoped to the appropriate environment.
Implement Caching and Optimization: The agent configures dependency caching (npm, pip, Maven) and build artifact caching to reduce pipeline execution time. Matrix builds are used to test across multiple language versions or operating systems in parallel. The agent also sets up conditional execution so that expensive stages like end-to-end tests only run on relevant branches.
Configure Deployment Strategies: The agent implements the appropriate deployment strategy based on the project's risk tolerance and infrastructure. Options include rolling updates, blue/green deployments (two identical environments swapped at the load balancer), and canary releases (gradual traffic shifting). The agent also configures rollback procedures in case a deployment fails health checks.
Set Up Notifications and Monitoring: The agent configures post-pipeline notifications to inform the team of build status via Slack, Microsoft Teams, email, or custom webhooks. Deployment events are logged, and the agent can integrate with monitoring tools to verify application health after each deployment.
Provide the agent with your project's language, framework, repository host, target deployment environment, and any specific requirements such as testing frameworks or deployment strategies.
Example prompt:
Set up a CI/CD pipeline for my Node.js Express app hosted on GitHub.
- Run ESLint and Prettier checks, then Jest unit tests
- Build a Docker image and push to GitHub Container Registry
- Deploy to AWS ECS staging on push to develop, production on push to main
- Send Slack notifications on failurename: CI/CD Pipeline
on:
push:
branches: [main, develop]
pull_request:
branches: [main]
env:
NODE_VERSION: '20'
REGISTRY: ghcr.io
IMAGE_NAME: ${{ github.repository }}
jobs:
lint:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with:
node-version: ${{ env.NODE_VERSION }}
cache: 'npm'
- run: npm ci
- run: npm run lint
- run: npm run format:check
test:
runs-on: ubuntu-latest
needs: lint
strategy:
matrix:
node-version: [18, 20, 22]
services:
postgres:
image: postgres:16
env:
POSTGRES_PASSWORD: testpass
POSTGRES_DB: testdb
ports:
- 5432:5432
options: >-
--health-cmd pg_isready
--health-interval 10s
--health-timeout 5s
--health-retries 5
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with:
node-version: ${{ matrix.node-version }}
cache: 'npm'
- run: npm ci
- run: npm test -- --coverage
env:
DATABASE_URL: postgres://postgres:testpass@localhost:5432/testdb
- uses: actions/upload-artifact@v4
with:
name: coverage-${{ matrix.node-version }}
path: coverage/
build-and-push:
runs-on: ubuntu-latest
needs: test
if: github.event_name == 'push'
permissions:
contents: read
packages: write
steps:
- uses: actions/checkout@v4
- uses: docker/login-action@v3
with:
registry: ${{ env.REGISTRY }}
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }}
- uses: docker/build-push-action@v5
with:
context: .
push: true
tags: |
${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:${{ github.sha }}
${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:latest
cache-from: type=gha
cache-to: type=gha,mode=max
deploy-staging:
runs-on: ubuntu-latest
needs: build-and-push
if: github.ref == 'refs/heads/develop'
environment: staging
steps:
- uses: aws-actions/configure-aws-credentials@v4
with:
aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
aws-region: us-east-1
- run: |
aws ecs update-service --cluster staging-cluster \
--service my-app --force-new-deployment
deploy-production:
runs-on: ubuntu-latest
needs: build-and-push
if: github.ref == 'refs/heads/main'
environment: production
steps:
- uses: aws-actions/configure-aws-credentials@v4
with:
aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
aws-region: us-east-1
- run: |
aws ecs update-service --cluster production-cluster \
--service my-app --force-new-deployment
notify:
runs-on: ubuntu-latest
needs: [deploy-staging, deploy-production]
if: always() && contains(needs.*.result, 'failure')
steps:
- uses: slackapi/slack-github-action@v1.25.0
with:
payload: |
{"text": "Pipeline failed for ${{ github.repository }} on ${{ github.ref_name }}"}
env:
SLACK_WEBHOOK_URL: ${{ secrets.SLACK_WEBHOOK_URL }}stages:
- lint
- test
- build
- deploy
variables:
PIP_CACHE_DIR: "$CI_PROJECT_DIR/.pip-cache"
DOCKER_IMAGE: $CI_REGISTRY_IMAGE:$CI_COMMIT_SHA
cache:
paths:
- .pip-cache/
- .venv/
lint:
stage: lint
image: python:3.12-slim
script:
- pip install ruff mypy
- ruff check src/
- mypy src/ --ignore-missing-imports
test:
stage: test
image: python:3.12-slim
services:
- postgres:16
variables:
POSTGRES_DB: testdb
POSTGRES_PASSWORD: testpass
DATABASE_URL: "postgresql://postgres:testpass@postgres:5432/testdb"
script:
- python -m venv .venv
- source .venv/bin/activate
- pip install -r requirements.txt -r requirements-dev.txt
- pytest tests/ --cov=src --cov-report=xml
artifacts:
reports:
coverage_report:
coverage_format: cobertura
path: coverage.xml
build:
stage: build
image: docker:24
services:
- docker:24-dind
script:
- docker login -u $CI_REGISTRY_USER -p $CI_REGISTRY_PASSWORD $CI_REGISTRY
- docker build -t $DOCKER_IMAGE -t $CI_REGISTRY_IMAGE:latest .
- docker push $DOCKER_IMAGE
- docker push $CI_REGISTRY_IMAGE:latest
deploy_production:
stage: deploy
image: alpine:latest
only:
- main
environment:
name: production
url: https://myapp.example.com
before_script:
- apk add --no-cache openssh-client
- eval $(ssh-agent -s)
- echo "$SSH_PRIVATE_KEY" | ssh-add -
script:
- ssh deploy@production-server "docker pull $DOCKER_IMAGE && docker-compose up -d"actions/checkout@v4, python:3.12-slim) to ensure reproducible builds and avoid supply-chain attacks.retry directive for individual jobs.paths: or GitLab changes:) to scope pipeline triggers.© seb1n, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in devops-and-infrastructure/ci-cd of seb1n/awesome-ai-agent-skills.
Open the folder on GitHubat commit 75865a5
CI CD 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| CI CD this skillseb1n/awesome-ai-agent-skills | 206 | — | ~2.9k | Automated safety check: Pass | MIT | |
| Fingerprint CI Gateliarjsdev/liarjs-skills | 518 | 1 repos | ~986 | Automated safety check: Notes | MIT | |
| Megatron-LM Base Image BumpNVIDIA/Megatron-LM | 18k | — | ~2.8k | Automated safety check: Pass | Apache-2.0 | |
| Megatron-LM CI/CD GuideNVIDIA/Megatron-LM | 18k | — | ~1.8k | Automated safety check: Pass | Apache-2.0 | |
| Megalinter Checknvuillam/npm-groovy-lint | 248 | 1 repos | ~3.9k | Automated safety check: Notes | MIT | |
| Migrate To TeamcityJetBrains/teamcity-cli | 125 | — | ~1.3k | Automated safety check: Pass | Apache-2.0 |
liarjsdev/liarjs-skills
Gate a build on browser fingerprint regressions with liarjs - save a baseline scan as JSON, diff later runs against it, and fail the job when the consistency score falls below a floor.
NVIDIA/Megatron-LM
Moves Megatron-LM CI to a newer NVIDIA PyTorch base image, updating both the GitHub and GitLab pins together and handling the CI follow-up.
NVIDIA/Megatron-LM
Explains Megatron-LM's CI pipeline, PR scope labels, triggering the internal GitLab CI with a dry run first, and investigating CI failures.
nvuillam/npm-groovy-lint
Collect MegaLinter lint errors for the current repository. An agent skill from nvuillam/npm-groovy-lint.
JetBrains/teamcity-cli
Migrating CI/CD pipelines to TeamCity. An agent skill from JetBrains/teamcity-cli.
Wide-Moat/open-computer-use
Explore GitLab repositories using glab CLI and git commands.
seb1n/awesome-ai-agent-skills
Plan, execute, document, and retest authorized security assessments of AI agents and multi-agent workflows using safe adversarial cases, synthetic identities, canaries, and evidence-based findings.
seb1n/awesome-ai-agent-skills
Build a preliminary, evidence-based EU AI Act readiness assessment across AI-system inventory, territorial scope, operator roles, prohibited-practice screening, risk classification, transparency…
seb1n/awesome-ai-agent-skills
Design and verify auditable human oversight, approval gates, escalation paths, and safe state transitions for AI agent workflows.
seb1n/awesome-ai-agent-skills
Design, implement, harden, and verify Model Context Protocol (MCP) servers with precise tool contracts, least-privilege authorization, safe transports, structured errors, and interoperability tests.
seb1n/awesome-ai-agent-skills
Inspect, extract, OCR, create, merge, split, reorder, rotate, annotate, fill, redact, compress, secure, and verify PDF documents while preserving source files and visual fidelity.
seb1n/awesome-ai-agent-skills
Audit agent skills, plugins, prompts, manifests, scripts, dependencies, and bundled assets for provenance, prompt-injection, permission, execution, exfiltration, persistence, and update risk.
Works with
Categories
Set up a continuous integration and continuous delivery (CI/CD) pipeline for a software project, automating builds, tests, and deployments across environments. CI CD is an agent skill from seb1n/awesome-ai-agent-skills. Set up a continuous integration and continuous delivery (CI/CD) pipeline for a software project, automating builds, tests, and deployments across environments.
CI CD fits situations like: the user requests ci cd; provides relevant inputs for this workflow.
Run `npx skills add seb1n/awesome-ai-agent-skills --skill ci-cd -a claude-code`. Or copy the skill folder (devops-and-infrastructure/ci-cd in seb1n/awesome-ai-agent-skills) into .claude/skills/ci-cd in your project. Claude Code loads it when a task matches its description.
Run `npx skills add seb1n/awesome-ai-agent-skills --skill ci-cd -a codex`. Or copy the skill folder (devops-and-infrastructure/ci-cd in seb1n/awesome-ai-agent-skills) into .agents/skills/ci-cd in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add seb1n/awesome-ai-agent-skills --skill ci-cd -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ci-cd, .gemini/skills/ci-cd, .github/skills/ci-cd and .opencode/skills/ci-cd in your project.
Going by SKILL.md and its folder, CI CD needs credentials named POSTGRES_PASSWORD, AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY and GITHUB_TOKEN. Our summary lists: Python 3; Node.js; Docker; A credential in GITHUB_TOKEN; A credential in AWS_SECRET_ACCESS_KEY.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
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.
CI CD is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.9k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with CI CD: Fingerprint CI Gate (liarjsdev/liarjs-skills, 518 stars), Megatron-LM Base Image Bump (NVIDIA/Megatron-LM, 18k stars), Megatron-LM CI/CD Guide (NVIDIA/Megatron-LM, 18k stars) and Megalinter Check (nvuillam/npm-groovy-lint, 248 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
seb1n (a GitHub user) maintains it in seb1n/awesome-ai-agent-skills, which has 206 GitHub stars. The repository holds 92 skills in this directory. The repository was last updated on August 9, 2026.
Source: seb1n/awesome-ai-agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.