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 nimadorostkar/Claude-Skills-collection --skill secrets-managementgit clone --depth 1 https://github.com/nimadorostkar/Claude-Skills-collectionWrote 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/nimadorostkar/claude-skills-collection/secrets-management)<a href="https://agentmods.dev/skills/nimadorostkar/claude-skills-collection/secrets-management"><img src="https://agentmods.dev/badge/skills/nimadorostkar/claude-skills-collection/secrets-management/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/nimadorostkar/claude-skills-collection/secrets-management"><img src="https://agentmods.dev/badge/skills/nimadorostkar/claude-skills-collection/secrets-management.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00039 | $0.01242 |
| Opus 5 | $0.00019 | $0.00621 |
| Sonnet 5 | $0.00008 | $0.00248 |
| Haiku 4.5 | $0.00004 | $0.00124 |
Grade A, and why
secrets-management 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 9d 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 — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Secrets Management
Purpose
Keep credentials out of code, out of logs, and out of git history — and be able to rotate them quickly when, inevitably, one leaks.
When to Use
- Setting up secret storage for an application.
- A secret has been committed or exposed.
- Implementing rotation.
- Auditing a repository or a running system for exposed credentials.
Capabilities
- Secret storage: cloud secret managers, Vault, sealed secrets.
- Injection: environment, mounted files, SDK-based retrieval.
- Rotation, including zero-downtime rotation of database credentials.
- Leak detection in code, history, logs, and error reports.
- Incident response for an exposed secret.
Inputs
- The secrets an application needs, and their blast radius if leaked.
- The runtime and how it can receive them.
- The rotation capability of each upstream provider.
Outputs
- No secrets in the repository, the image, or the logs.
- Secrets injected at runtime from a managed store.
- A rotation procedure that has been tested.
Workflow
- Eliminate static credentials first — Prefer workload identity: IAM roles, OIDC federation, managed identities. A secret that does not exist cannot leak. This is the single most effective change available.
- Store what remains in a secret manager — Never in code, never in a config file in the repository, never in a container image layer.
- Inject at runtime — Mounted file or environment variable, fetched from the manager at start. The application never contains the value.
- Redact in logs — Structured logging with a redaction filter on known secret field names, and never logging the full request body of an auth endpoint.
- Scan continuously — A pre-commit hook and a CI scan on the full history. Detection after the fact is far better than not detecting it.
- Rotate on a schedule and on exposure — And test the rotation before you need it in an emergency.
Best Practices
- A secret committed to git is compromised the moment it is pushed, regardless of whether the repository is private, whether it was force-pushed away, or whether anyone noticed. Rotate it. Deleting the commit is not a remediation.
- Environment variables are visible in
/proc, in crash dumps, in some error reporters, and to any process running as the same user. A mounted file with restricted permissions is stronger. - Rotation must be zero-downtime: support two valid credentials simultaneously (issue the new one, deploy, revoke the old one). A rotation that requires an outage will not be done.
- Never pass a secret as a command-line argument. It is visible in
psto every user on the host. - Do not build a secret into a container image, even in a "private" registry. Image layers are extractable with
docker historyand are cached in many places. - Short-lived, dynamically generated credentials (Vault's database secrets engine, IAM database authentication) make rotation continuous and leak impact minimal.
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.
- 9d ago First seen · 121 lines · 39 tokens per session scan A 6110f3416b42
secrets-management is a skill published in the GitHub repository nimadorostkar/Claude-Skills-collection (26 stars, last pushed 25d ago), licensed MIT. It adds 39 tokens to every session and 1,242 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 2026-09-03.
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