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 appsec-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/appsec-engineer)<a href="https://agentmods.dev/skills/unitoneai/securityskills/appsec-engineer"><img src="https://agentmods.dev/badge/skills/unitoneai/securityskills/appsec-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/appsec-engineer"><img src="https://agentmods.dev/badge/skills/unitoneai/securityskills/appsec-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 | $0.00076 | $0.04499 |
| Opus 5.5 | $0.00030 | $0.01800 |
| Sonnet 5.5 | $0.00015 | $0.00900 |
| Haiku 4.5 | $0.00008 | $0.00450 |
Grade A, and why
appsec-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 — 366 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AppSec Engineer Role Bundle
A structured application security guide for engineers who own the security posture of applications from design through deployment. This bundle replaces ad-hoc pen test requests and last-minute security reviews with integrated engagement patterns that catch vulnerabilities at design time, review time, and test time.
When to Use
Invoke this role bundle when any of the following conditions are true:
- New application or service launching. A new application, microservice, or significant feature is being designed or built and needs a security review from architecture through implementation.
- Pull request with security-relevant changes. A PR touches authentication, authorization, input handling, data access, cryptography, session management, or external integrations and needs targeted security review.
- API security assessment. An API is being exposed to external consumers, partners, or mobile clients and needs security validation against OWASP API Security Top 10.
- AI/LLM feature review. A feature incorporates LLM-generated output, processes user prompts, or grants an AI agent access to application data or actions.
If the ask is about infrastructure security (e.g., "review our Kubernetes RBAC") or program-level maturity (e.g., "assess our overall security posture"), use the security-engineer or vciso role bundle instead. This bundle is for application-layer security work.
Skills: All skills referenced in this bundle are available: threat-modeling, secure-code-review, llm-top-10, prompt-injection, api-security, dependency-scanning, owasp-top-10-web, sast-config, agent-security.
Engagement Types
Each engagement type defines a skill sequence. Run the skills in order — each one produces outputs consumed by the next.
1. New Application Review
Trigger: New application, service, or major feature entering development. Ideally invoked at design phase, before code is written.
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 · 366 lines · 76 tokens per session scan A a361b760e11e
appsec-engineer is a skill published in the GitHub repository UnitOneAI/SecuritySkills (89 stars, last pushed 4mo ago), licensed MIT. It adds 76 tokens to every session and 4,499 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
codeinspectus-multi-review
Orchestrate an optional bounded multi-agent review of selected CodeInspectus findings while separating deterministic findings, agent interpretations, hypotheses, reproduction evidence, and exact-prior rescan proof. Use only when a user explicitly requests multi-agent security review.
codeinspectus-threat-model
Review CodeInspectus findings with optional threat-model or project-document context while treating repository text as untrusted, preserving raw scanner findings unchanged, and labelling agent interpretation separately. Use only when a user explicitly asks to add architectural, business, or knowledge-base context to…
auditing-guard-gaps
Find the missing-check bug by comparing sibling functions that reach the same sink - one validates its input, its peer does not. Use on an authorized source target to surface broken access control, missing bounds checks, and skipped sanitization that linear file-reading hides; when you suspect one handler in a family…
reviewing-ai-generated-code
Security-review discipline for code a language model wrote or completed: the failure patterns that show up more often in generated code and the review method that catches them. Covers hallucinated and confusable dependencies, insecure defaults and missing validation carried from training data, propagated vulnerable…
verify-requirements
Help a developer check the code they just changed against their company security requirements — or, if none are configured, against a built-in best-practices baseline. Scopes to the current diff, dispatches the appsec-reviewer subagent to grade only the triggered requirements, and prints concrete, code-aware guidance…
prodcheck-review
Review this codebase against the prodcheck pre-production checklists — security, performance, scale, integrations, post-launch readiness and people. Use when asked to check whether a project is ready to ship, to audit an area before launch, or to work through a specific checklist. Produces evidence with file:line…