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 UnitOneAI/SecuritySkills --skill security-engineergit 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/security-engineer)<a href="https://agentmods.dev/skills/unitoneai/securityskills/security-engineer"><img src="https://agentmods.dev/badge/skills/unitoneai/securityskills/security-engineer/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/unitoneai/securityskills/security-engineer"><img src="https://agentmods.dev/badge/skills/unitoneai/securityskills/security-engineer.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00072 | $0.03952 |
| Opus 5.5 | $0.00029 | $0.01581 |
| Sonnet 5.5 | $0.00014 | $0.00790 |
| Haiku 4.5 | $0.00007 | $0.00395 |
Grade A, and why
security-engineer 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 1mo 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 — 361 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Security Engineer Role Bundle
A structured engineering guide for embedding security into products, pipelines, and infrastructure. This bundle replaces one-off security reviews with repeatable engagement patterns that produce hardened systems, verified remediations, and measurable reduction in vulnerability surface.
When to Use
Invoke this role bundle when any of the following conditions are true:
- Code review needed. A new feature, service, or significant code change requires security review before merging or deploying. The review needs to go beyond linting — it requires understanding of the application's threat model.
- CI/CD pipeline hardening. The engineering team wants to secure the software delivery pipeline: build integrity, secrets management, dependency verification, container image security, and deployment controls.
- Vulnerability response. A new CVE affects the organization's stack, a scanner has produced findings that need triage and prioritization, or a penetration test report needs remediation planning.
- Infrastructure security review. A new environment, cloud account, or infrastructure change requires security validation — IAM policies, firewall rules, container configurations, or network segmentation.
If the ask is a program-level concern (e.g., "assess our overall security maturity"), use the vciso role bundle instead. This bundle is for hands-on engineering work.
Skills: All skills referenced in this bundle are available: secure-code-review, cve-triage, pipeline-security, iam-review, threat-modeling, dependency-scanning, sast-config, secrets-management, container-security, patch-prioritization, scanner-tuning, firewall-review.
Engagement Types
Each engagement type defines a skill sequence. Run the skills in order — each one produces outputs consumed by the next.
1. Code Review
Trigger: New feature branch, pull request with security-sensitive changes, or pre-release security review of a service.
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.
- 1mo ago First seen · 361 lines · 72 tokens per session scan A f15f6387fc70
security-engineer is a skill published in the GitHub repository UnitOneAI/SecuritySkills (85 stars, last pushed 3mo ago), licensed MIT. It adds 72 tokens to every session and 3,952 once invoked, about $0.0003 per session on Opus 5.5. 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.
Other skills, from other repositories
hunting-cicd-workflow-injection
Hunt a CI/CD pipeline for attacker-controlled repository data that reaches a privileged execution context, after the trigger and the token scope are resolved. Covers an untrusted event field (an issue or pull-request title, a branch name, a commit message) interpolated directly into a run-step shell command, a…
auditing-cicd-oidc-trust
Audit continuous-integration pipelines for the trust they extend to untrusted input: workflows that run on incoming change requests from forks while holding repository secrets, steps that let attacker-controlled content reach a privileged command, and cloud role trust conditions that accept a pipeline's short-lived…
hunting-supply-chain-risks
Hunt for the ways an attacker gets code into your build without touching your repo: dependency confusion (a public package shadowing an internal name), typosquatting and slopsquatting (a package named after a model's hallucination), poisoned pipeline execution (untrusted input running as a build step), and…
analyzing-github-ci-performance
Computes a CI/CD metrics table from raw GitHub Actions records for one repository over the last 30 days, including failure rates and developer waiting time. Use for historical CI performance questions or the first-experience repository demo. For currently failing checks, use reporting-github-ci-failures.
repair-github-ci
Fix failing GitHub CI / Actions checks via fixgithubprci and push to the existing PR head, or fix a branch's failing CI via a linked repair worktree.
scheduling-github-ci-repairs
Sets up ongoing local monitoring of one repository's open pull requests, automatically editing, testing, and pushing fixes for failing GitHub Actions checks. Offers a disposable private-repository demonstration. Use for recurring PR repair or the local CI onboarding demo.