Goldsky Secrets Management

Create and manage secrets for pipeline sink credentials.

Agent Instructions

When this skill is invoked, follow this streamlined workflow:

Step 1: Verify Login + List Existing Secrets

Run goldsky secret list to confirm authentication and show existing secrets.

If authentication fails: Invoke the auth-setup skill first.

Step 2: Determine Intent Quickly

Skip unnecessary questions. If the user's intent is clear from context, proceed directly:

User says "create a postgres secret" → Go straight to credential collection
User pastes a connection string → Parse it immediately (see Connection String Parsing)
User mentions a specific provider (Neon, Supabase, etc.) → Use provider-specific guidance

Only use AskUserQuestion if intent is genuinely unclear.

Step 3: Connection String Parsing (Preferred for PostgreSQL)

If user provides a connection string, parse it directly instead of asking questions.

PostgreSQL connection string format:

postgres://USER:PASSWORD@HOST:PORT/DATABASE?sslmode=require
postgresql://USER:PASSWORD@HOST/DATABASE

Parsing logic:

Extract: user, password, host, port (default 5432), databaseName
Construct JSON immediately
Create the secret without further questions

Example - user provides:

postgresql://neondb_owner:abc123@ep-cool-name.us-east-2.aws.neon.tech/neondb?sslmode=require

Create using the connection string directly:

goldsky secret create --name SUGGESTED_NAME
# When prompted, paste the connection string:
# postgresql://neondb_owner:abc123@ep-cool-name.us-east-2.aws.neon.tech/neondb?sslmode=require

Step 4: Provider-Specific Quick Paths

Neon:

Connection string format: postgresql://USER:PASS@ep-XXX.REGION.aws.neon.tech/neondb
Default port: 5432
Common issue: Free tier has 512MB limit - pipelines will fail with "project size limit exceeded"

Supabase:

Connection string format: postgresql://postgres:PASS@db.PROJECT.supabase.co:5432/postgres
Use the "Connection string" from Project Settings → Database

PlanetScale (MySQL):

Use "protocol": "mysql" and port 3306

Step 5: Create Secret Directly

Once you have credentials (from parsing or user input), create immediately:

goldsky secret create \
  --name SECRET_NAME \
  --value '{"type":"jdbc","protocol":"postgres",...}' \
  --description "Optional description"

Naming convention: PROJECT_PROVIDER (e.g., TRADEWATCH_NEON, ANALYTICS_SUPABASE)

Step 6: Verify

Run goldsky secret list to confirm creation.

Secret JSON Schemas

JSON schema files are available in the schemas/ folder. Each file contains the full schema with examples.

Secret Type	Schema File	Type Field	Use Case
PostgreSQL	`postgres.json`	`jdbc`	Database sink
MySQL	`postgres.json`	`jdbc`	Database sink (protocol: mysql)
ClickHouse	`clickhouse.json`	`clickHouse`	Analytics database
Kafka	`kafka.json`	`kafka`	Event streaming
AWS S3	`s3.json`	`s3`	Object storage
ElasticSearch	`elasticsearch.json`	`elasticSearch`	Search engine
DynamoDB	`dynamodb.json`	`dynamodb`	NoSQL database
SQS	`sqs.json`	`sqs`	Message queue
OpenSearch	`opensearch.json`	`opensearch`	Search/analytics
Webhook	`webhook.json`	`httpauth`	HTTP endpoints

Schema location: schemas/ (relative to this skill's directory)

Quick Reference Examples

PostgreSQL — Connection string format:

postgres://username:password@host:port/database

goldsky secret create --name MY_POSTGRES_SECRET
# The CLI will prompt for the connection string interactively

ClickHouse — Connection string format:

https://username:password@host:port/database

Kafka — JSON format:

{
  "type": "kafka",
  "bootstrapServers": "broker:9092",
  "securityProtocol": "SASL_SSL",
  "saslMechanism": "PLAIN",
  "saslJaasUsername": "user",
  "saslJaasPassword": "pass"
}

S3 — Colon-separated format:

access_key_id:secret_access_key

Or with session token: access_key_id:secret_access_key:session_token

Webhook:

Note: Turbo pipeline webhook sinks do not support Goldsky's native secrets management. Include auth headers directly in the pipeline YAML headers: field instead.

Connection String Parser

For PostgreSQL, use the helper script to parse connection strings:

./scripts/parse-connection-string.sh "postgresql://user:pass@host:5432/dbname"
# Output: JSON ready for goldsky secret create --value

Step 5: Confirm and Create

Show the user what will be created (mask password with ***) and ask for confirmation before running the command.

Step 6: Verify Success

Run goldsky secret list to confirm the secret was created.

Quick Reference

Action	Command
Create	`goldsky secret create --name NAME --value "value"`
List	`goldsky secret list`
Reveal	`goldsky secret reveal NAME`
Update	`goldsky secret update NAME --value "new-value"`
Delete	`goldsky secret delete NAME`

Prerequisites

Goldsky CLI installed
Logged in (goldsky login)
Connection credentials for your target sink

Why Secrets Are Needed

Pipelines that write to external sinks (PostgreSQL, ClickHouse, Kafka, S3) need credentials to connect. Instead of putting credentials directly in your pipeline YAML, you store them as secrets and reference them by name.

Benefits:

Credentials are encrypted and stored securely
Pipeline configs can be shared without exposing secrets
Credentials can be rotated without modifying pipelines

Command Reference

Command	Purpose	Key Flags
`goldsky secret create`	Create a new secret	`--name`, `--value`, `--description`
`goldsky secret list`	List all secrets
`goldsky secret reveal <name>`	Show secret value
`goldsky secret update <name>`	Update secret value	`--value`, `--description`
`goldsky secret delete <name>`	Delete a secret	`-f` (force, skip confirmation)

Common Patterns

PostgreSQL Secret

goldsky secret create --name PROD_POSTGRES
# When prompted, provide the connection string:
# postgres://admin:secret@db.example.com:5432/mydb

Pipeline usage:

sinks:
  output:
    type: postgres
    from: my_source
    schema: public
    table: transfers
    secret_name: PROD_POSTGRES

ClickHouse Secret

goldsky secret create --name CLICKHOUSE_ANALYTICS
# When prompted, provide the connection string:
# https://default:secret@abc123.clickhouse.cloud:8443/analytics

Pipeline usage:

sinks:
  output:
    type: clickhouse
    from: my_source
    table: events
    secret_name: CLICKHOUSE_ANALYTICS
    primary_key: id

Rotating Credentials

Update an existing secret without changing pipeline configs:

goldsky secret update MY_POSTGRES_SECRET --value 'postgres://admin:NEW_PASSWORD@db.example.com:5432/mydb'

Active pipelines will pick up the new credentials on their next connection.

Deleting Unused Secrets

# With confirmation prompt
goldsky secret delete OLD_SECRET

# Skip confirmation (for scripts)
goldsky secret delete OLD_SECRET -f

Warning: Deleting a secret that's in use will cause pipeline failures.

Secret Naming Conventions

Use descriptive, uppercase names with underscores:

Good	Bad
`PROD_POSTGRES_MAIN`	`secret1`
`STAGING_CLICKHOUSE`	`my-secret`
`KAFKA_PROD_CLUSTER`	`postgres`

Include environment and purpose in the name for clarity.

Troubleshooting

Error: Secret not found

Error: Secret 'MY_SECRET' not found

Cause: The secret name doesn't exist or is misspelled.
Fix: Run goldsky secret list to see available secrets and check the exact name.

Error: Secret already exists

Error: Secret 'MY_SECRET' already exists

Cause: Attempting to create a secret with a name that's already in use.
Fix: Use goldsky secret update MY_SECRET --value "new-value" to update, or choose a different name.

Error: Invalid secret value format

Error: Invalid JSON in secret value

Cause: JSON syntax error in the secret value.
Fix: Validate your JSON before creating the secret:

# Test JSON validity
echo '{"url":"...","user":"..."}' | jq .

Pipeline fails with "connection refused"

Cause: The credentials in the secret are incorrect or the database is unreachable.
Fix:

Verify credentials work outside Goldsky: psql "postgresql://..."
Check the secret value: goldsky secret reveal MY_SECRET
Ensure the database allows connections from Goldsky's IP ranges

Pipeline fails with "authentication failed"

Cause: Username or password in the secret is incorrect. Fix: Update the secret with correct credentials:

goldsky secret update MY_SECRET --value 'postgres://correct:credentials@host:5432/db'

Secret value contains special characters

Cause: JSON strings with special characters need proper escaping. Fix: Use proper JSON escaping for special characters in password fields:

Backslash: use \\
Double quote: use \"
Newline: use \n

With the structured JSON format, most special characters in passwords work without URL encoding since the password is a separate field.

/turbo-builder — Build and deploy pipelines that use these secrets
/auth-setup — Invoke this if user is not logged in
/turbo-pipelines — Pipeline YAML configuration reference

secrets