secrets-management

sickn33/antigravity-awesome-skills · updated Apr 8, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill secrets-management
0 commentsdiscussion
summary

Secure secrets management practices for CI/CD pipelines using Vault, AWS Secrets Manager, and other tools.

skill.md

Secrets Management

Secure secrets management practices for CI/CD pipelines using Vault, AWS Secrets Manager, and other tools.

Purpose

Implement secure secrets management in CI/CD pipelines without hardcoding sensitive information.

Use this skill when

  • Store API keys and credentials
  • Manage database passwords
  • Handle TLS certificates
  • Rotate secrets automatically
  • Implement least-privilege access

Do not use this skill when

  • You plan to hardcode secrets in source control
  • You cannot secure access to the secrets backend
  • You only need local development values without sharing

Instructions

  1. Identify secret types, owners, and rotation requirements.
  2. Choose a secrets backend and access model.
  3. Integrate CI/CD or runtime retrieval with least privilege.
  4. Validate rotation and audit logging.

Safety

  • Never commit secrets to source control.
  • Limit access and log secret usage for auditing.

Secrets Management Tools

HashiCorp Vault

  • Centralized secrets management
  • Dynamic secrets generation
  • Secret rotation
  • Audit logging
  • Fine-grained access control

AWS Secrets Manager

  • AWS-native solution
  • Automatic rotation
  • Integration with RDS
  • CloudFormation support

Azure Key Vault

  • Azure-native solution
  • HSM-backed keys
  • Certificate management
  • RBAC integration

Google Secret Manager

  • GCP-native solution
  • Versioning
  • IAM integration

HashiCorp Vault Integration

Setup Vault

# Start Vault dev server
vault server -dev

# Set environment
export VAULT_ADDR='http://127.0.0.1:8200'
export VAULT_TOKEN='root'

# Enable secrets engine
vault secrets enable -path=secret kv-v2

# Store secret
vault kv put secret/database/config username=admin password=secret

GitHub Actions with Vault

name: Deploy with Vault Secrets

on: [push]

jobs:
  deploy:
    runs-on: ubuntu-latest
    steps:
    - uses: actions/checkout@v4

    - name: Import Secrets from Vault
      uses: hashicorp/vault-action@v2
      with:
        url: https://vault.example.com:8200
        token: ${{ secrets.VAULT_TOKEN }}
        secrets: |
          secret/data/database username | DB_USERNAME ;
          secret/data/database password | DB_PASSWORD ;
          secret/data/api key | API_KEY

    - name: Use secrets
      run: |
        echo "Connecting to database as $DB_USERNAME"
        # Use $DB_PASSWORD, $API_KEY

GitLab CI with Vault

deploy:
  image: vault:latest
  before_script:
    - export VAULT_ADDR=https://vault.example.com:8200
    - export VAULT_TOKEN=$VAULT_TOKEN
    - apk add curl jq
  script:
    - |
      DB_PASSWORD=$(vault kv get -field=password secret/database/config)
      API_KEY=$(vault kv get -field=key secret/api/credentials)
      echo "Deploying with secrets..."
      # Use $DB_PASSWORD, $API_KEY

Reference: See references/vault-setup.md

AWS Secrets Manager

Store Secret

aws secretsmanager create-secret \
  --name production/database/password \
  --secret-string "super-secret-password"

Retrieve in GitHub Actions

- name: Configure AWS credentials
  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-west-2

- name: Get secret from AWS
  run: |
    SECRET=$(aws secretsmanager get-secret-value \
      --secret-id production/database/password \
      --query SecretString \
      --output text)
    echo "::add-mask::$SECRET"
    echo "DB_PASSWORD=$SECRET" >> $GITHUB_ENV

- name: Use secret
  run: |
    # Use $DB_PASSWORD
    ./deploy.sh

Terraform with AWS Secrets Manager

data "aws_secretsmanager_secret_version" "db_password" {
  secret_id = "production/database/password"
}

resource "aws_db_instance" "main" {
  allocated_storage    = 100
  engine              = "postgres"
  instance_class      = "db.t3.large"
  username            = "admin"
  password            = jsondecode(data.aws_secretsmanager_secret_version.db_password.secret_string)["password"]
}

GitHub Secrets

Organization/Repository Secrets

- name: Use GitHub secret
  run: |
    echo "API Key: ${{ secrets.API_KEY }}"
    echo "Database URL: ${{ secrets.DATABASE_URL }}"

Environment Secrets

deploy:
  runs-on: ubuntu-latest
  environment: production
  steps:
  - name: Deploy
    run: |
      echo "Deploying with ${{ secrets.PROD_API_KEY }}"

Reference: See references/github-secrets.md

GitLab CI/CD Variables

Project Variables

deploy:
  script:
    - echo "Deploying with $API_KEY"
    - echo "Database: $DATABASE_URL"

Protected and Masked Variables

  • Protected: Only available in protected branches
  • Masked: Hidden in job logs
  • File type: Stored as file

Best Practices

  1. Never commit secrets to Git
  2. Use different secrets per environment
  3. Rotate secrets regularly
  4. Implement least-privilege access
  5. Enable audit logging
  6. Use secret scanning (GitGuardian, TruffleHog)
  7. Mask secrets in logs
  8. Encrypt secrets at rest
  9. Use short-lived tokens when possible
  10. Document secret requirements

Secret Rotation

Automated Rotation with AWS

import boto3
import json

def lambda_handler(event, context):
    client = boto3.client('secretsmanager')

    # Get current secret
    response = client.get_secret_value(SecretId='my-secret')
    current_secret = json.loads(response['SecretString'])

    # Generate new password
    new_password = generate_strong_password()

    # Update database password
    update_database_password(new_password)

    # Update secret
    client.put_secret_value(
        SecretId='my-secret',
        SecretString=json.dumps({
            'username': current_secret['username'],
            'password': new_password
        })
    )

    return {'statusCode': 200}

Manual Rotation Process

  1. Generate new secret
  2. Update secret in secret store
  3. Update applications to use new secret
  4. Verify functionality
  5. Revoke old secret

External Secrets Operator

Kubernetes Integration

apiVersion: external-secrets.io/v1beta1
kind: SecretStore
metadata:
  name: vault-backend
  namespace: production
spec:
  provider:
    vault:
      server: "https://vault.example.com:8200"
      path: "secret"
      version: "v2"
      auth:
        kubernetes:
          mountPath
how to use secrets-management

How to use secrets-management on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add secrets-management
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill secrets-management

The skills CLI fetches secrets-management from GitHub repository sickn33/antigravity-awesome-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/secrets-management

Reload or restart Cursor to activate secrets-management. Access the skill through slash commands (e.g., /secrets-management) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.474 reviews
  • Ishan Mensah· Dec 20, 2024

    secrets-management is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Sophia Yang· Dec 20, 2024

    We added secrets-management from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Emma Kim· Dec 16, 2024

    secrets-management fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Luis Brown· Dec 12, 2024

    I recommend secrets-management for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Aarav Mehta· Dec 8, 2024

    secrets-management reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Tariq Johnson· Dec 8, 2024

    Solid pick for teams standardizing on skills: secrets-management is focused, and the summary matches what you get after install.

  • Chinedu Verma· Nov 27, 2024

    Registry listing for secrets-management matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Diya Reddy· Nov 27, 2024

    secrets-management has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Tariq Wang· Nov 23, 2024

    I recommend secrets-management for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Dev Robinson· Nov 19, 2024

    Keeps context tight: secrets-management is the kind of skill you can hand to a new teammate without a long onboarding doc.

showing 1-10 of 74

1 / 8