doppler-workflows
$
npx mdskill add terrylica/cc-skills/doppler-workflows> **Self-Evolving Skill**: This skill improves through use. If instructions are wrong, parameters drifted, or a workaround was needed — fix this file immediately, don't defer. Only update for real, reproducible issues.
SKILL.md
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---
name: doppler-workflows
description: Manage credentials and secrets through Doppler for publishing and deployment workflows. Use whenever the user needs to publish Python packages.
allowed-tools: Read, Bash
---
# Doppler Credential Workflows
> **Self-Evolving Skill**: This skill improves through use. If instructions are wrong, parameters drifted, or a workaround was needed — fix this file immediately, don't defer. Only update for real, reproducible issues.
## When to Use This Skill
Use this skill when:
- 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
## Quick Reference
## 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
<!-- ADR: 2025-12-10-clickhouse-skill-documentation-gaps -->
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.
---
## Troubleshooting
| Issue | Cause | Solution |
| -------------------------- | -------------------------------- | ----------------------------------------------------- |
| 403 on PyPI publish | Token expired or wrong scope | Regenerate project-scoped token, update in Doppler |
| InvalidClientTokenId (AWS) | Access key rotated or deleted | Run AWS key rotation workflow, update Doppler |
| Variable expands empty | Using `$VAR` without --command | Always use `--command='...$VAR...'` pattern |
| Doppler CLI not found | Not installed | `brew install dopplerhq/cli/doppler` |
| Wrong config selected | Ambiguous project/config | Specify both `--project` and `--config` explicitly |
| mise [env] not loading | Not in directory with .mise.toml | `cd` to project directory or check mise.toml path |
| Secret retrieval slow | No caching configured | Use mise `cache()` with duration for repeated access |
| Token length mismatch | Copied with extra whitespace | Trim token: `echo -n 'secret' \| doppler secrets set` |
## Post-Execution Reflection
After this skill completes, check before closing:
1. **Did the command succeed?** — If not, fix the instruction or error table that caused the failure.
2. **Did parameters or output change?** — If the underlying tool's interface drifted, update Usage examples and Parameters table to match.
3. **Was a workaround needed?** — If you had to improvise (different flags, extra steps), update this SKILL.md so the next invocation doesn't need the same workaround.
Only update if the issue is real and reproducible — not speculative.
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