Doppler Workflows

---
name: doppler-workflows
description: Doppler credential and publishing workflows. TRIGGERS - PyPI publish, AWS credentials, Doppler secrets.
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:**

```bash
doppler 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

---

## Quick Start Examples

### PyPI Publishing

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

### AWS Operations

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

---

## 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

---

## Reference Documentation

For detailed information, see:

- [PyPI Publishing](./references/pypi-publishing.md) - Token setup, publishing, troubleshooting
- [AWS Credentials](./references/aws-credentials.md) - Rotation workflow, setup, troubleshooting
- [Multi-Service Patterns](./references/multi-service-patterns.md) - Multiple PyPI packages, multiple AWS accounts
- [AWS Workflow](./AWS_WORKFLOW.md) - Complete AWS credential management guide

**Bundled Specifications:**

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

---

## Using mise [env] for Local Development (Recommended)

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

```toml
# .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](../../../itp/skills/mise-configuration/SKILL.md) for complete patterns.

---

## PyPI Publishing Policy

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For PyPI publishing, see [`pypi-doppler` skill](../../../itp/skills/pypi-doppler/SKILL.md) for **LOCAL-ONLY** workspace policy.

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