doppler-secret-validation
Doppler Secret Validation
Overview
Workflow for securely adding, validating, and testing API tokens and credentials in Doppler secrets management.
When to Use This Skill
Use this skill when:
- User provides API tokens or credentials (PyPI, GitHub, AWS, etc.)
- User mentions "add to Doppler", "store secret", "validate token"
- User wants to test authentication before production use
- User needs to verify secret storage and retrieval
Workflow
Step 1: Test Token Format (Before Adding to Doppler)
Before storing in Doppler, validate token format:
# Check token format, length, prefix
python3 -c "token = 'TOKEN_VALUE'; print(f'Prefix: {token[:20]}...'); print(f'Length: {len(token)}')"
Common token formats:
- PyPI:
pypi-...(179 chars) - GitHub:
ghp_...(40+ chars) - AWS: 20-char access key + 40-char secret
Step 2: Add Secret to Doppler
doppler secrets set SECRET_NAME="value" --project PROJECT --config CONFIG
Example:
doppler secrets set PYPI_TOKEN="pypi-AgEI..." \
--project claude-config --config prd
Important: CLI doesn't support --note. Add notes via dashboard:
- https://dashboard.doppler.com
- Navigate: PROJECT → CONFIG → SECRET_NAME
- Edit → Add descriptive note
Step 3: Validate Storage
Use the bundled validation script:
/usr/bin/env bash << 'VALIDATE_EOF'
cd ${CLAUDE_PLUGIN_ROOT}/skills/doppler-secret-validation
uv run scripts/validate_secret.py \
--project PROJECT \
--config CONFIG \
--secret SECRET_NAME
VALIDATE_EOF
This validates:
- Secret exists in Doppler
- Secret retrieval works
- Environment injection works via
doppler run
Example:
uv run scripts/validate_secret.py \
--project claude-config \
--config prd \
--secret PYPI_TOKEN
Step 4: Test API Authentication
Use the bundled auth test script (adapt test_api_authentication() for specific API):
/usr/bin/env bash << 'CONFIG_EOF'
cd ${CLAUDE_PLUGIN_ROOT}/skills/doppler-secret-validation
doppler run --project PROJECT --config CONFIG -- \
uv run scripts/test_api_auth.py \
--secret SECRET_NAME \
--api-url API_ENDPOINT
CONFIG_EOF
Example (PyPI):
doppler run --project claude-config --config prd -- \
uv run scripts/test_api_auth.py \
--secret PYPI_TOKEN \
--api-url https://upload.pypi.org/legacy/
Step 5: Document Usage
After validation, document the usage pattern for the user:
/usr/bin/env bash << 'CONFIG_EOF_2'
# Pattern 1: Doppler run (recommended for CI/scripts)
doppler run --project PROJECT --config CONFIG -- COMMAND
# Pattern 2: Manual export (for troubleshooting)
export SECRET_NAME=$(doppler secrets get SECRET_NAME \
--project PROJECT --config CONFIG --plain)
CONFIG_EOF_2
Step 5b: mise [env] Integration (Recommended for Local Development)
For multi-account GitHub setups or per-directory credential needs, integrate Doppler secrets with mise [env]:
# .mise.toml
[env]
# Option A: Direct Doppler CLI fetch (slower, always fresh)
GH_TOKEN = "{{ exec(command='doppler secrets get GH_TOKEN --project myproject --config prd --plain') }}"
GITHUB_TOKEN = "{{ exec(command='doppler secrets get GH_TOKEN --project myproject --config prd --plain') }}"
# Option B: Cache for performance (1 hour cache)
GH_TOKEN = "{{ cache(key='gh_token', duration='1h', run='doppler secrets get GH_TOKEN --project myproject --config prd --plain') }}"
GITHUB_TOKEN = "{{ cache(key='gh_token', duration='1h', run='doppler secrets get GH_TOKEN --project myproject --config prd --plain') }}"
Note: Set BOTH GH_TOKEN and GITHUB_TOKEN - different tools check different variable names (gh CLI vs npm scripts).
Why mise [env]? Doppler doppler run is session-scoped; mise [env] provides directory-scoped credentials that persist across commands.
See mise-configuration skill for complete patterns.
Common Patterns
Multiple Configs (dev, stg, prd)
Add secret to multiple environments:
# Production
doppler secrets set TOKEN="prod-value" --project foo --config prd
# Development
doppler secrets set TOKEN="dev-value" --project foo --config dev
Verify Secret Across Configs
/usr/bin/env bash << 'CONFIG_EOF_3'
for config in dev stg prd; do
echo "=== $config ==="
doppler secrets get TOKEN --project foo --config $config --plain | head -c 20
echo "..."
done
CONFIG_EOF_3
Security Guidelines
- Never log full secrets: Use
${SECRET:0:20}...masking - Prefer doppler run: Scopes secrets to single command
- Use --plain only for piping: Human-readable view masks secrets
- Separate configs per environment: dev/stg/prd isolation
Bundled Resources
- scripts/validate_secret.py - Complete validation suite (existence, retrieval, injection)
- scripts/test_api_auth.py - Template for API authentication testing
- references/doppler-patterns.md - Common CLI patterns and examples
Reference
- Doppler docs: https://docs.doppler.com/docs
- CLI install:
brew install dopplerhq/cli/doppler - See doppler-patterns.md for comprehensive patterns
Troubleshooting
| Issue | Cause | Solution |
|---|---|---|
| Secret not found | Wrong project/config specified | Verify with doppler secrets ls --project X --config |
| Auth test fails with 401 | Token expired or invalid | Regenerate token, re-add to Doppler |
| doppler run hangs | CLI waiting for input | Add --no-interactive flag |
| Token prefix mismatch | Wrong token type used | Check expected format (pypi-, ghp-, AKIA, etc.) |
| Validation script not found | Wrong directory context | Ensure CLAUDE_PLUGIN_ROOT is set correctly |
| Secret retrieval empty | Secret name typo | List secrets: doppler secrets ls --project X |
| mise cache stale | Duration expired | Clear cache or reduce duration setting |
| Multiple configs confusion | Secrets differ across envs | Use explicit --config flag for each command |