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Doppler Workflows

BSecurity

Manage credentials and secrets through Doppler for publishing and deployment workflows. Use whenever the user needs to publish Python packages.

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  • Added February 7, 2026
toolspythonshellbashawsgitci/cdsecuritydocumentation

Works with

  • cli

Security analysis

B75/100
  • criticalSends environment variables or credentials to an external URL

Pro scans all 7 files and shows the line behind each finding

Scanned September 24, 2026

npx -y skills add terrylica/cc-skills --skill doppler-workflows --agent claude-code

Installs into .claude/skills of the current project.

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SKILL.md
---
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

---

## Local Development: Directory-Scoped Doppler Config

For local development, bind the project directory to its Doppler project/config once, then scope each command with `doppler run`:

```bash
cd ~/project && doppler setup --project claude-config --config prd --no-interactive
doppler run -- COMMAND   # secrets such as PYPI_TOKEN exist for this command only
```

For a value needed across several commands in one shell, export it explicitly: `export PYPI_TOKEN="$(doppler secrets get PYPI_TOKEN --plain)"`.

> **Do NOT inject GitHub tokens this way (ADR 2026-06-21).** GitHub multi-account auth is driven by the repo's `origin` host-alias (`git@github.com-<account>:…`). A token resolves fresh per-repo via `~/.claude/tools/bin/gh-token-for-repo`; an ambient `GH_TOKEN` outranks the isolated gh profile and 401s after a rotation. The `.secrets/gh-token-*` files are deleted.

---

## 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    |
| Wrong project picked up    | Directory not bound or bound wrongly | `doppler configure` to inspect; re-run `doppler setup` |
| Secret retrieval slow      | One `doppler secrets get` per call | Fetch once per shell with `export VAR="$(doppler secrets get VAR --plain)"` |
| 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.

Files in this skill

  • AWS_SPECIFICATION.yaml6.9 KB
  • AWS_WORKFLOW.md10.6 KB
  • PYPI_REFERENCE.yaml19 KB
  • SKILL.md4.6 KB
  • references/aws-credentials.md2.3 KB
  • references/multi-service-patterns.md662 B
  • references/pypi-publishing.md1.7 KB

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