secrets-manager

A guide for keeping passwords, API keys, access tokens, and other secrets out of source code and handling them safely. It covers storing, delivering, rotating, and responding to exposed credentials.

In plain words
What is it for?
Use it to choose secret storage, inject secrets through environment variables or secret stores, plan key rotation, scan for hardcoded credentials, and remediate leaked secrets.
Why use it?
It reduces the risk of credentials being committed to a repository or exposed publicly. It also clarifies what to do when a secret has already leaked, including revoking or replacing it before cleaning up the code.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/jayrha/agentskills/secrets-manager
Any agent
npx skills add JayRHa/AgentSkills --skill secrets-manager
Clone the repo
git clone --depth 1 https://github.com/JayRHa/AgentSkills

Made for: Claude Code, Codex.

Per session 112 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,690 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00112 $0.01690
Opus 5 $0.00056 $0.00845
Sonnet 5 $0.00022 $0.00338
Haiku 4.5 $0.00011 $0.00169

Measured 2d ago against content hash b947aade0503, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

secrets-manager 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 2d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/install_precommit.sh, scripts/scan_secrets.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

secrets-manager/SKILL.md · 91 lines

How it starts

The opening of the file, as written. The whole thing — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Secrets Manager

Overview

This skill governs the full lifecycle of secrets: keeping them out of source code, storing them in the right backend, injecting them at runtime, rotating them on schedule, and remediating leaks fast and completely. A leaked credential is an active incident — assume it is compromised the moment it touches a public surface.

Keywords: secret, credential, API key, token, password, .env, environment variable, vault, HashiCorp Vault, KMS, envelope encryption, AWS Secrets Manager, GCP Secret Manager, Azure Key Vault, SOPS, sealed-secrets, rotation, key rotation, git-secrets, gitleaks, trufflehog, pre-commit hook, scrub, BFG, git filter-repo, hardcoded credentials, dotenv, OIDC, workload identity, leaked key.

Workflow

  1. Classify the request into one of four modes (see Decision Framework):

    • PREVENT — keep new secrets out of code.
    • STORE/INJECT — choose a backend and runtime delivery.
    • ROTATE — establish rotation cadence and automation.
    • REMEDIATE — a secret has already leaked.
  2. If a secret may already be exposed, treat it as REMEDIATE first. Rotation/revocation precedes cleanup. Removing the secret from git does NOT un-leak it. Follow references/leak-remediation.md step by step.

  3. Scan before you advise. Run scripts/scan_secrets.py over the repo (or recommend gitleaks/trufflehog for git history). Never assume the codebase is clean. Report findings with file, line, and a redacted match — never echo full secret values into logs, chat, or commits.

  4. Pick a storage backend using the matrix in references/storage-backends.md. Match to the runtime (local dev, CI, Kubernetes, serverless, VM) and the org's existing cloud. Prefer short-lived, dynamically-issued credentials and OIDC/workload identity over long-lived static keys wherever possible.

  5. Define injection. Secrets reach the process via environment variables, mounted files (tmpfs), or a fetch-at-startup SDK call — never baked into images, never committed. Use templates/dotenv-template.md for local dev and document .env in .gitignore.

Read the full file on GitHub · 91 lines

Files

What ships with it

7 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.

Changes

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.

  1. 2d ago First seen · 91 lines · 112 tokens per session scan A b947aade0503

Subscribe to this mod's changes

secrets-manager is a skill published in the GitHub repository JayRHa/AgentSkills (4 stars, last pushed 1mo ago), licensed MIT. It adds 112 tokens to every session and 1,690 once invoked, about $0.0006 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 2026-08-31.

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