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 agentmods add skills/unitoneai/securityskills/secrets-managementnpx skills add UnitOneAI/SecuritySkills --skill secrets-managementgit clone --depth 1 https://github.com/UnitOneAI/SecuritySkillsWrote 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/unitoneai/securityskills/secrets-management)<a href="https://agentmods.dev/skills/unitoneai/securityskills/secrets-management"><img src="https://agentmods.dev/badge/skills/unitoneai/securityskills/secrets-management.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00082 | $0.05267 |
| Opus 5 | $0.00041 | $0.02634 |
| Sonnet 5 | $0.00016 | $0.01053 |
| Haiku 4.5 | $0.00008 | $0.00527 |
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 6d 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 — 489 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Secrets Management Review
A structured, repeatable process for evaluating secrets management practices against the OWASP Secrets Management Cheat Sheet and NIST SP 800-57 Part 1 Rev 5 (Recommendation for Key Management). This skill covers secret detection patterns, rotation automation, vault and cloud secrets manager integration, agent-specific credential handling, .env file exposure, and git history secret leaks. All findings reference framework controls with severity ratings and actionable remediation.
Important: This skill analyzes detection patterns and configuration practices. It never extracts, logs, or displays actual secret values. All regex patterns shown are for detection tooling configuration, not for secret extraction.
When to Use
If a target is provided via arguments, focus the review on: $ARGUMENTS
- Security review of application repositories for hardcoded credentials.
- Evaluation of secrets management architecture (Vault, AWS Secrets Manager, GCP Secret Manager, Azure Key Vault).
- CI/CD pipeline credential hygiene assessment.
- Incident response after a secret exposure event.
- Compliance audits requiring NIST SP 800-57 key management alignment.
- Architecture review of agentic systems that require credential access.
Context
OWASP identifies hardcoded secrets as a persistent, high-impact vulnerability. The OWASP Secrets Management Cheat Sheet defines secrets as "digital authentication credentials that grant access to systems or data," including API keys, passwords, certificates, and encryption keys. NIST SP 800-57 Part 1 Rev 5 Section 5.3 establishes cryptoperiods -- the time span during which a specific key is authorized for use. Secrets that exceed their cryptoperiod without rotation represent both a compliance gap and an operational risk. In agentic and automated environments, the challenge intensifies: autonomous agents require credential access but should never hold long-lived secrets.
Process
Step 1: Discovery -- Locate Secret-Adjacent Files
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.
- 6d ago First seen · 489 lines · 82 tokens per session scan A d95159aa2543
secrets-management is a skill published in the GitHub repository UnitOneAI/SecuritySkills (59 stars, last pushed 2mo ago), licensed MIT. It adds 82 tokens to every session and 5,267 once invoked, about $0.0004 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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