Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add terrylica/cc-skills --skill doppler-secret-validationgit clone --depth 1 https://github.com/terrylica/cc-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/terrylica/cc-skills/doppler-secret-validation)<a href="https://agentmods.dev/skills/terrylica/cc-skills/doppler-secret-validation"><img src="https://agentmods.dev/badge/skills/terrylica/cc-skills/doppler-secret-validation/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/terrylica/cc-skills/doppler-secret-validation"><img src="https://agentmods.dev/badge/skills/terrylica/cc-skills/doppler-secret-validation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 148 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Prompt Injection · line 199 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00031 | $0.01808 |
| Opus 5 | $0.00015 | $0.00904 |
| Sonnet 5 | $0.00006 | $0.00362 |
| Haiku 4.5 | $0.00003 | $0.00181 |
Grade A, and why
doppler-secret-validation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 221 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Doppler Secret Validation
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.
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'
ROOT="$(cc-plugin-root devops-tools)"
cd "$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
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 221 lines · 31 tokens per session scan A 44f3ad3523b5
doppler-secret-validation is a skill published in the GitHub repository terrylica/cc-skills (72 stars, last pushed yesterday), licensed MIT. It adds 31 tokens to every session and 1,808 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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