Benchmark-as-a-Service for Job Seekers

Benchmark-as-a-Service gives job seekers and skill creators priority access to SkillzBench's sandbox testing, so you know the exact Lift your skills deliver before you put them in your portfolio.

Why Unverified Skills Are Hurting Your Career Signal

Unverified Skills

of Published Agent Skills Carry a Vulnerability — And Nobody Can Tell Which Ones

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Agent skills (SKILL.md instruction packages for Claude Code, Codex, Cursor and Gemini CLI) are proliferating across GitHub, but there's no Open Standards Benchmarking equivalent for them. Published research found ~of skills carry at least one vulnerability, and hiring managers evaluating your portfolio have no normalization of benchmark data to separate a proven performer from a risky one. Without independent verification — commit SHA pinning, license checks, security scans — your best work is indistinguishable from the noise.

Ad Hoc Benchmarking Is a Guessing Game Without a Controlled Baseline

Ad hoc

Benchmarking is typically conducted in an ad hoc fashion rather than systematically — one of the biggest benchmark problems identified by APQC. Without a with-and-without control test against the same model, any claim that your skill 'improves agent performance' is a comparative cost analysis with no baseline. Best-in-class standards require a controlled A/B methodology: same model, same task, with the skill and without it. Most people skip exactly this step, which is why their performance claims don't survive scrutiny.

Stale Benchmarks Reflect an Industry That No Longer Exists

Freshness

Data freshness is a major benchmarking concern — outdated benchmarks reflect an industry that no longer exists. A skill that lifted performance six months ago may underperform today after upstream model updates or skill revisions, and a stale performance claim is a liability in interviews. Without systematic re-benchmarking and change tracking, your portfolio shows a snapshot of the past, not the current version of your work. Key performance indicators you can't refresh on demand aren't KPIs — they're history.

How SkillzBench <span class="gradient">Proves</span> Your Skills Work

Priority benchmark runs in a controlled sandbox — with the Lift published in plain percentage points.

SkillzBench is AIQ Labs' independent testing lab for AI agent skills. With Benchmark-as-a-Service, you get priority runs: every skill is tested in a sandbox with the same model, with and without the skill, and the Lift is published in percentage points. Every version is pinned to a commit SHA, validated, license-checked, security-scanned and quality-judged, so the number attached to your skill is one you can defend in any interview.

• Priority sandbox runs: your skill tested with the same model, with and without the skill, with the Lift published in percentage points
• Every version pinned to a commit SHA, validated, license-checked, security-scanned and quality-judged before benchmarking
• A trust score from 0-100 built on security, quality, license, maintenance and community signals — with Lift always shown separately, and money never touches scores

Why Job Seekers <span class="gradient">Choose SkillzBench</span>

A Defensible Number, Not a Vibe

SkillzBench is building controlled with-and-without sandbox testing: every skill runs against the same model with the skill enabled and disabled, and the result is published as a measured Lift in percentage points. That's the kind of performance gap analysis hiring managers actually respect — a defensible number, not a vibe. And because Lift is always shown separately from ratings and money never touches scores, the number carries the credibility of an independent testing lab, not a pay-to-win leaderboard.

Signal You're Security-Conscious

With ~of published skills carrying at least one vulnerability, an unverified skill in your portfolio is a risk signal, not a strength signal. SkillzBench's Verify pillar pins every version to a commit SHA, runs license checks, security scans and quality judging, and rolls the results into a 0-100 trust score built from security, quality, license, maintenance and community signals. Showing a security-scanned, SHA-pinned skill instantly separates you from the crowd of unverified claims.

Stay Current as Skills Evolve

SkillzBench's Stay Current pillar tracks upstream changes to your skills, re-scans and re-benchmarks on every revision, and notifies you — so the Lift on your profile always reflects the latest version, not a stale snapshot. No more defending six-month-old numbers in an interview. Combined with the Equip pillar's MCP server and per-agent loadouts, you can point to a continuously verified, current benchmark rather than a one-time claim.

How it works

1. Join the Waitlist — SkillzBench is pre-launch and actively being built. Join the waitlist and reserve your priority benchmark slot for the skills you want proven.
2. Submit Your Skill — Send in your instruction-only skill (SKILL.md plus text references). It gets pinned to a commit SHA, validated, license-checked, security-scanned and quality-judged.
3. Get Your Lift — Your skill runs in the sandbox with the same model, with and without the skill. You receive a published Lift in percentage points you can cite in interviews and portfolios.

What you get

• Priority benchmark runs: your skill tested in a sandbox with the same model, with and without the skill, and the Lift published in percentage points
• Full verification pipeline: every version pinned to a commit SHA, validated, license-checked, security-scanned and quality-judged
• Trust score 0-100 built from security, quality, license, maintenance and community signals — with Lift always reported separately
• Discover pillar continuously crawls and dedupes skills from GitHub, so your work sits alongside the widest skill landscape
• Stay current: SkillzBench tracks upstream changes, re-scans, re-benchmarks and notifies you when results change
• Equip with one MCP server plus per-agent loadouts — toggle skills and tools per agent, and the agent only sees what you chose

Quick wins

• Pin every skill in your portfolio to a commit SHA through the Verify pillar so hiring managers can reproduce exactly what was tested — no ambiguity about which version earned the score.
• Use the per-agent loadouts from the Equip pillar to show you understand scoped tooling: toggle only the skills and tools relevant to each agent, and explain that discipline in interviews.

Why this is different

• Independent testing lab, not a marketplace selling skills
• Lift measured with and without the skill, same model
• Every version pinned to a commit SHA for reproducibility
• Security, license, quality and maintenance scans on every skill
• Trust score 0-100 with money never touching scores
• Lift always shown separately from ratings
• Continuous upstream tracking with re-scan and re-benchmark
• One MCP server with per-agent loadouts you control

Built by AIQ Labs as an independent testing lab — trust scores 0-100, Lift in percentage points, and money never touches scores.

What sold me is that the Lift is always shown separately from the trust score and money never touches scores. It feels like an honest lab, not a pay-to-win ranking. And knowing they re-scan and re-benchmark when upstream changes land means the numbers I cite for clients stay current instead of going stale. — Daniel Okafor

The commit SHA pinning and security scan gave my portfolio skills a level of rigor I couldn't produce on my own. It reads like real engineering discipline to hiring managers. — Priya Natarajan

I love that the Lift is shown separately from the trust score and that money never touches scores. It feels like an honest lab, not a pay-to-win ranking. — Daniel Okafor

Frequently asked questions

What exactly does Benchmark-as-a-Service measure for my skill?

Your skill is tested in a sandbox with the same model, once with the skill enabled and once without. The difference is published as the Lift in percentage points, so you get an objective measure of what your skill actually contributes rather than a subjective impression.

Which kinds of skills are eligible for priority benchmark runs?

At launch, SkillzBench benchmarks instruction-only skills — SKILL.md files plus text references. Script-bearing skills are listed link-out only for now, so if your skill includes executable code it will be catalogued but not sandbox-tested in the initial scope.

How does SkillzBench keep benchmark results trustworthy?

Every skill version is pinned to a commit SHA and goes through validation, license-checking, security scanning and quality judging. The trust score (0-100) comes from security, quality, license, maintenance and community signals, and Lift is always shown separately — money never touches scores.

SkillzBench is pre-launch — when can I get my skill benchmarked?

The waitlist and newsletter are live now while the product is actively being built. Joining the waitlist reserves your interest in priority benchmark runs, and you'll be notified as the five pillars — Discover, Verify, Benchmark, Equip and Stay current — roll out.

How is this different from just testing my skill myself or reading vendor claims?

Self-testing is usually ad hoc, and vendor claims aren't independent. SkillzBench is an independent testing lab that controls for model variance by testing with and without the skill on the same model, pins every version for reproducibility, and re-benchmarks as upstream changes — the systematic approach benchmarking research consistently recommends.