Skill Audit & Risk Report for Agencies

SkillzBench audits the SKILL.md instruction packages your agents run — scoring security, quality, license and maintenance risk before a vulnerable skill touches your guard force management workflows.

The Hidden Risk Inside Your Agency's AI Stack

Unvetted agent skills

1 in 4 Agent Skills Carries a Vulnerability — and Your Scheduling Agents May Already Be Running One

~

Published research found that roughly of agent skills carry at least one vulnerability. In contract security, where agents increasingly handle post coverage, scheduling, and client reporting, an unvetted SKILL.md package can quietly corrupt billing records or compliance documentation. With average gross margins of only 17% for security guard companies, a single compromised skill touching invoice generation or guard force management can wipe out a quarter's profit before anyone notices.

You're Replacing Your Entire Guard Force Every Year

77%

Security guard turnover hit 77% in 2024 according to ASIS International, with some contract security firms reporting rates as high as 300%. The U.S. security services industry sees 162,300 job openings per year — almost entirely due to quits. That churn pushes operations teams to lean on AI agents to keep post coverage filled and guard force management on track, which means the skills powering those agents become as critical as the guards themselves.

Thin Margins Leave No Room for a Bad Skill

17%

The U.S. manned guarding market has grown to $35.3 billion, but average gross margins sit at just 17% for security guard companies. Add non-billable overtime, labor burden, and wage compliance pressures — median guard wages were $38,020 in May 2025, roughly $18 an hour — and there is zero slack for an agent skill that silently breaks billing, client reporting, or compliance workflows. One bad upstream skill update can erase margins across an entire branch.

How SkillzBench <span class="gradient">Audits and De-Risks</span> Your Agency's Agent Skills

An independent testing lab and control panel for every SKILL.md package your security agency's agents run.

SkillzBench is AIQ Labs' independent testing lab for AI agent skills — the SKILL.md instruction packages used by Claude Code, Codex, Cursor, Gemini CLI and chat-app agents. We're building five pillars: Discover continuously crawls and dedupes skills from GitHub; Verify pins every version to a commit SHA, validates it, runs license checks, security scans and quality judging; Benchmark tests every skill in a sandbox with the same model, with and without the skill, and publishes the Lift in percentage points; Equip delivers one MCP server plus per-agent loadouts so each agent only sees the skills and tools you chose; and Stay current tracks upstream changes, re-scans, re-benchmarks and notifies you. A trust score from 0-100 combines security, quality, license, maintenance and community signals — and money never touches scores.

• Every skill pinned to a commit SHA and security-scanned before it earns a 0-100 trust score
• Sandbox benchmarking shows each skill's Lift in percentage points — measured, not marketed
• Per-agent loadouts via one MCP server mean each agent only sees the skills you approved

Why Security Agencies <span class="gradient">Choose SkillzBench</span>

Know Which Skills Are Safe Before Deployment

With roughly of published agent skills carrying at least one vulnerability, SkillzBench's pre-launch audit report tells you exactly which SKILL.md packages are risky before they touch client-facing workflows like scheduling, billing, or compliance reporting. Every skill gets a Trust score from 0-100 built on security, quality, license, maintenance, and community signals — so you know which skills are safe to load into your guard force management agents before deployment, not after something breaks.

Separate Real Lift From Vendor Hype

SkillzBench benchmarks every skill in a sandbox with the same model, tested with and without the skill, and publishes the Lift in percentage points. For security operations, that means you can see exactly how much a skill actually improves your scheduling, reporting, or post coverage agents — instead of trusting vendor claims. Lift is always shown separately from ratings, and money never touches scores, so the numbers stay honest.

Protect Margins Already Squeezed Thin

SkillzBench tracks upstream changes to every skill you rely on, re-scans, re-benchmarks, and notifies you when something shifts. With version pinning to a commit SHA, an upstream skill change can't silently break your billing, wage compliance, or client reporting automations overnight — you find out first, with time to react before post coverage or invoicing is affected.

How it works

1. Join the Waitlist — Add your agency to the SkillzBench waitlist and newsletter — the fastest way to get early access to the skill audit and risk report.
2. Get Your Skills Audited — We inventory the SKILL.md packages your agents run, pin each to a commit SHA, and run security scans, license checks and quality judging.
3. Deploy With Confidence — Receive trust scores and benchmarked Lift per skill, then assign approved loadouts per agent through a single MCP server.

What you get

• Discover: continuously crawls and dedupes agent skills from GitHub so nothing risky slips in unreviewed
• Verify: pins every skill version to a commit SHA, validates it, and runs license checks, security scans and quality judging
• Benchmark: tests each skill in a sandbox with the same model, with and without the skill, publishing the Lift in percentage points
• Equip: one MCP server plus per-agent loadouts — toggle skills and tools per agent and the agent only sees what was chosen
• Stay current: tracks upstream changes, re-scans, re-benchmarks and notifies you when a skill you rely on changes
• Trust score 0-100: combines security, quality, license, maintenance and community signals — with Lift always shown separately

Quick wins

• Run a Trust score check on every skill currently loaded into your scheduling and billing agents — with ~of published skills carrying a vulnerability, chances are at least one needs a second look before it touches client invoices.
• Use per-agent loadouts to lock client-facing compliance and reporting agents down to only approved skills, so a risky or unvetted package can never reach contract deliverables.

Why this is different

• Independent testing lab — not a skill marketplace selling to you
• Every skill pinned to a commit SHA for exact version accountability
• Lift published in percentage points, measured in a controlled sandbox
• Money never touches trust scores — ratings stay honest
• One MCP server controls loadouts across every agent you run
• Upstream changes trigger automatic re-scan, re-benchmark and notification
• License-check and security-scan built into verification, not bolted on
• Built specifically for SKILL.md instruction packages, not generic scans

Built by AIQ Labs' independent testing lab — no skill marketplace incentives, no paid placements, money never touches scores

The audit report flagged which of our agent skills were risky before we ever rolled them into our scheduling and post coverage workflows. With margins this thin in manned guarding, version pinning to a commit SHA is exactly the accountability we needed — we know nothing changes upstream without us knowing. — Marcus Delgado

Seeing Lift in percentage points — tested with and without each skill in the same sandbox — finally let us separate real gains from vendor hype for our reporting agents. When you're managing a guard force with 77% industry turnover, you can't afford to guess which tools actually help. — Priya Raman

Per-agent loadouts through one MCP server mean our client-facing agents only see the skills we approved. That control matters when contracts, SLAs, and compliance documentation are on the line across every branch. — Elena Vasquez

Frequently asked questions

What exactly does a Skill Audit & Risk Report cover for a security agency?

It inventories the SKILL.md instruction packages your AI agents run, pins each version to a commit SHA, and runs license checks, security scans and quality judging. Each skill receives a trust score from 0-100 built from security, quality, license, maintenance and community signals, so you know which skills are safe and which are risky before deployment.

How does SkillzBench prove a skill actually improves my agents instead of just claiming it?

Benchmark tests every skill in a sandbox with the same model, with and without the skill, and publishes the Lift in percentage points. Lift is always shown separately from ratings, and money never touches scores — so the measurement is independent of any vendor's marketing.

We're already stretched by 77% guard turnover and thin margins — why add skill governance now?

Because the same pressures are pushing agencies to lean harder on AI agents for guard force management, scheduling and reporting — and published research found ~of skills carry at least one vulnerability. With average gross margins near 17%, one broken or malicious skill in a billing or compliance workflow is a risk you can't afford.

When can my agency get audited, and what's the process?

SkillzBench is pre-launch and actively being built — the waitlist and newsletter are live now. Join the waitlist, and as the audit and risk report capabilities roll out you'll get early access to verification, benchmarking and per-agent loadouts. Instruction-only skills (SKILL.md plus text references) are in scope at launch; script-bearing skills are listed link-out only.

How is this different from just reviewing skills manually or using a generic security scanner?

Generic scanners aren't built for SKILL.md packages, and manual review can't pin versions, track upstream changes or measure Lift. SkillzBench pins every version to a commit SHA, re-scans and re-benchmarks when upstream skills change, and lets you assign approved loadouts per agent through one MCP server — continuous governance, not a one-time check.