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name: doppler-workflows description: Manages credentials and publishing workflows via Doppler. Use when publishing Python packages to PyPI, rotating AWS credentials, or managing secrets with Doppler. allowed-tools: Read, Bash

Doppler Credential Workflows

Quick Reference

When to use this skill:

• Publishing Python packages to PyPI
• Rotating AWS access keys
• Managing credentials across multiple services
• Troubleshooting authentication failures (403, InvalidClientTokenId)
• Setting up Doppler credential injection patterns
• Multi-token/multi-account strategies

Core Pattern: Doppler CLI

Standard Usage:

Copydoppler run --project <project> --config <config> --command='<command>'

Why --command flag:

• Official Doppler pattern (auto-detects shell)
• Ensures variables expand AFTER Doppler injects them
• Without it: shell expands $VAR before Doppler runs → empty string

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Quick Start Examples

PyPI Publishing

Copydoppler run --project claude-config --config dev \
  --command='uv publish --token "$PYPI_TOKEN"'

AWS Operations

Copydoppler run --project aws-credentials --config dev \
  --command='aws s3 ls --region $AWS_DEFAULT_REGION'

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Best Practices

1. Always use --command flag for credential injection
2. Use project-scoped tokens (PyPI) for better security
3. Rotate credentials regularly (90 days recommended)
4. Document with Doppler notes: doppler secrets notes set <SECRET> "<note>"
5. Use stdin for storing secrets: echo -n 'secret' | doppler secrets set
6. Test injection before using: echo ${#VAR} to verify length
7. Multi-token naming: SERVICE_TOKEN_{ABBREV} for clarity

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Reference Documentation

For detailed information, see:

• PyPI Publishing - Token setup, publishing, troubleshooting
• AWS Credentials - Rotation workflow, setup, troubleshooting
• Multi-Service Patterns - Multiple PyPI packages, multiple AWS accounts
• AWS Workflow - Complete AWS credential management guide

Bundled Specifications:

• PYPI_REFERENCE.yaml - Complete PyPI spec
• AWS_SPECIFICATION.yaml - AWS credential architecture

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Using mise [env] for Local Development (Recommended)

For local development, mise [env] provides a simpler alternative to doppler run:

Copy# .mise.toml
[env]
# Fetch from Doppler with caching for performance
PYPI_TOKEN = "{{ cache(key='pypi_token', duration='1h', run='doppler secrets get PYPI_TOKEN --project claude-config --config prd --plain') }}"

# For GitHub multi-account setups
GH_TOKEN = "{{ read_file(path=env.HOME ~ '/.claude/.secrets/gh-token-accountname') | trim }}"

When to use mise [env]:

• Per-directory credential configuration
• Multi-account GitHub setups
• Credentials that persist across commands (not session-scoped)

When to use doppler run:

• CI/CD pipelines
• Single-command credential scope
• When you want credentials auto-cleared after command

See mise-configuration skill for complete patterns.

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PyPI Publishing Policy

For PyPI publishing, see pypi-doppler skill for LOCAL-ONLY workspace policy.

Do NOT configure PyPI publishing in GitHub Actions or CI/CD pipelines.