Awesome-omni-skills secrets-management
Secrets Management workflow skill. Use this skill when the user needs Secure secrets management practices for CI/CD pipelines using Vault, AWS Secrets Manager, and other tools and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
git clone https://github.com/diegosouzapw/awesome-omni-skills
T=$(mktemp -d) && git clone --depth=1 https://github.com/diegosouzapw/awesome-omni-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/secrets-management" ~/.claude/skills/diegosouzapw-awesome-omni-skills-secrets-management && rm -rf "$T"
skills/secrets-management/SKILL.mdSecrets Management
Overview
This public intake copy packages
plugins/antigravity-awesome-skills-claude/skills/secrets-management from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.
Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.
This intake keeps the copied upstream files intact and uses
metadata.json plus ORIGIN.md as the provenance anchor for review.
Secrets Management Secure secrets management practices for CI/CD pipelines using Vault, AWS Secrets Manager, and other tools.
Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Purpose, Safety, Secrets Management Tools, HashiCorp Vault Integration, AWS Secrets Manager, GitHub Secrets.
When to Use This Skill
Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.
- Store API keys and credentials
- Manage database passwords
- Handle TLS certificates
- Rotate secrets automatically
- Implement least-privilege access
- You plan to hardcode secrets in source control
Operating Table
| Situation | Start here | Why it matters |
|---|---|---|
| First-time use | | Confirms repository, branch, commit, and imported path before touching the copied workflow |
| Provenance review | | Gives reviewers a plain-language audit trail for the imported source |
| Workflow execution | | Starts with the smallest copied file that materially changes execution |
| Supporting context | | Adds the next most relevant copied source file without loading the entire package |
| Handoff decision | | Helps the operator switch to a stronger native skill when the task drifts |
Workflow
This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.
- Identify secret types, owners, and rotation requirements.
- Choose a secrets backend and access model.
- Integrate CI/CD or runtime retrieval with least privilege.
- Validate rotation and audit logging.
- Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
- Read the overview and provenance files before loading any copied upstream support files.
- Load only the references, examples, prompts, or scripts that materially change the outcome for the current request.
Imported Workflow Notes
Imported: Instructions
- Identify secret types, owners, and rotation requirements.
- Choose a secrets backend and access model.
- Integrate CI/CD or runtime retrieval with least privilege.
- Validate rotation and audit logging.
Imported: Purpose
Implement secure secrets management in CI/CD pipelines without hardcoding sensitive information.
Examples
Example 1: Ask for the upstream workflow directly
Use @secrets-management to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.
Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.
Example 2: Ask for a provenance-grounded review
Review @secrets-management against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.
Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.
Example 3: Narrow the copied support files before execution
Use @secrets-management for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.
Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.
Example 4: Build a reviewer packet
Review @secrets-management using the copied upstream files plus provenance, then summarize any gaps before merge.
Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.
Best Practices
Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.
- Never commit secrets to Git
- Use different secrets per environment
- Rotate secrets regularly
- Implement least-privilege access
- Enable audit logging
- Use secret scanning (GitGuardian, TruffleHog)
- Mask secrets in logs
Imported Operating Notes
Imported: Best Practices
- Never commit secrets to Git
- Use different secrets per environment
- Rotate secrets regularly
- Implement least-privilege access
- Enable audit logging
- Use secret scanning (GitGuardian, TruffleHog)
- Mask secrets in logs
- Encrypt secrets at rest
- Use short-lived tokens when possible
- Document secret requirements
Troubleshooting
Problem: The operator skipped the imported context and answered too generically
Symptoms: The result ignores the upstream workflow in
plugins/antigravity-awesome-skills-claude/skills/secrets-management, fails to mention provenance, or does not use any copied source files at all.
Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Load only the files that materially change the answer, then restate the provenance before continuing.
Problem: The imported workflow feels incomplete during review
Symptoms: Reviewers can see the generated
SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task.
Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.
Problem: The task drifted into a different specialization
Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.
Related Skills
- Use when the work is better handled by that native specialization after this imported skill establishes context.@00-andruia-consultant-v2
- Use when the work is better handled by that native specialization after this imported skill establishes context.@10-andruia-skill-smith-v2
- Use when the work is better handled by that native specialization after this imported skill establishes context.@20-andruia-niche-intelligence-v2
- Use when the work is better handled by that native specialization after this imported skill establishes context.@2d-games
Additional Resources
Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.
| Resource family | What it gives the reviewer | Example path |
|---|---|---|
| copied reference notes, guides, or background material from upstream | |
| worked examples or reusable prompts copied from upstream | |
| upstream helper scripts that change execution or validation | |
| routing or delegation notes that are genuinely part of the imported package | |
| supporting assets or schemas copied from the source package | |
Imported Reference Notes
Imported: Reference Files
- HashiCorp Vault configurationreferences/vault-setup.md
- GitHub Secrets best practicesreferences/github-secrets.md
Imported: Safety
- Never commit secrets to source control.
- Limit access and log secret usage for auditing.
Imported: 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
Imported: 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
Imported: 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"] }
Imported: 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
Imported: GitLab CI/CD Variables
Project Variables
deploy: script: - echo "Deploying with $API_KEY" - echo "Database: $DATABASE_URL"
Protected and Masked Variables
- Protected: Only available in protected branches
- Masked: Hidden in job logs
- File type: Stored as file
Imported: Secret Rotation
Automated Rotation with AWS
import boto3 import json def lambda_handler(event, context): client = boto3.client('secretsmanager') # Get current secret response = client.get_secret_value(SecretId='my-secret') current_secret = json.loads(response['SecretString']) # Generate new password new_password = generate_strong_password() # Update database password update_database_password(new_password) # Update secret client.put_secret_value( SecretId='my-secret', SecretString=json.dumps({ 'username': current_secret['username'], 'password': new_password }) ) return {'statusCode': 200}
Manual Rotation Process
- Generate new secret
- Update secret in secret store
- Update applications to use new secret
- Verify functionality
- Revoke old secret
Imported: External Secrets Operator
Kubernetes Integration
apiVersion: external-secrets.io/v1beta1 kind: SecretStore metadata: name: vault-backend namespace: production spec: provider: vault: server: "https://vault.example.com:8200" path: "secret" version: "v2" auth: kubernetes: mountPath: "kubernetes" role: "production" --- apiVersion: external-secrets.io/v1beta1 kind: ExternalSecret metadata: name: database-credentials namespace: production spec: refreshInterval: 1h secretStoreRef: name: vault-backend kind: SecretStore target: name: database-credentials creationPolicy: Owner data: - secretKey: username remoteRef: key: database/config property: username - secretKey: password remoteRef: key: database/config property: password
Imported: Secret Scanning
Pre-commit Hook
#!/bin/bash # .git/hooks/pre-commit # Check for secrets with TruffleHog docker run --rm -v "$(pwd):/repo" \ trufflesecurity/trufflehog:latest \ filesystem --directory=/repo if [ $? -ne 0 ]; then echo "❌ Secret detected! Commit blocked." exit 1 fi
CI/CD Secret Scanning
secret-scan: stage: security image: trufflesecurity/trufflehog:latest script: - trufflehog filesystem . allow_failure: false
Imported: Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.