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/proffesor-for-testing/agentic-qe/agent-benchmark-suitenpx skills add proffesor-for-testing/agentic-qe --skill agent-benchmark-suitegit clone --depth 1 https://github.com/proffesor-for-testing/agentic-qeWrote 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/proffesor-for-testing/agentic-qe/agent-benchmark-suite)<a href="https://agentmods.dev/skills/proffesor-for-testing/agentic-qe/agent-benchmark-suite"><img src="https://agentmods.dev/badge/skills/proffesor-for-testing/agentic-qe/agent-benchmark-suite.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 | $0.00018 | $0.04197 |
| Opus 5 | $0.00009 | $0.02099 |
| Sonnet 5 | $0.00004 | $0.00839 |
| Haiku 4.5 | $0.00002 | $0.00420 |
Grade A, and why
agent-benchmark-suite 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.
This is a copy
100% identical to agent-benchmark-suite — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 670 lines — stays where its author put it; the contents beside it link to each section on GitHub.
name: Benchmark Suite type: agent category: optimization description: Comprehensive performance benchmarking, regression detection and performance validation
Benchmark Suite Agent
Agent Profile
- Name: Benchmark Suite
- Type: Performance Optimization Agent
- Specialization: Comprehensive performance benchmarking and testing
- Performance Focus: Automated benchmarking, regression detection, and performance validation
Core Capabilities
1. Comprehensive Benchmarking Framework
// Advanced benchmarking system
class ComprehensiveBenchmarkSuite {
constructor() {
this.benchmarks = {
// Core performance benchmarks
throughput: new ThroughputBenchmark(),
latency: new LatencyBenchmark(),
scalability: new ScalabilityBenchmark(),
resource_usage: new ResourceUsageBenchmark(),
// Swarm-specific benchmarks
coordination: new CoordinationBenchmark(),
load_balancing: new LoadBalancingBenchmark(),
topology: new TopologyBenchmark(),
fault_tolerance: new FaultToleranceBenchmark(),
// Custom benchmarks
custom: new CustomBenchmarkManager()
};
this.reporter = new BenchmarkReporter();
this.comparator = new PerformanceComparator();
this.analyzer = new BenchmarkAnalyzer();
}
// Execute comprehensive benchmark suite
async runBenchmarkSuite(config = {}) {
const suiteConfig = {
duration: config.duration || 300000, // 5 minutes default
iterations: config.iterations || 10,
warmupTime: config.warmupTime || 30000, // 30 seconds
cooldownTime: config.cooldownTime || 10000, // 10 seconds
parallel: config.parallel || false,
baseline: config.baseline || null
};
const results = {
summary: {},
detailed: new Map(),
baseline_comparison: null,
recommendations: []
};
// Warmup phase
await this.warmup(suiteConfig.warmupTime);
// Execute benchmarks
if (suiteConfig.parallel) {
results.detailed = await this.runBenchmarksParallel(suiteConfig);
} else {
results.detailed = await this.runBenchmarksSequential(suiteConfig);
}
// Generate summary
results.summary = this.generateSummary(results.detailed);
// Compare with baseline if provided
if (suiteConfig.baseline) {
results.baseline_comparison = await this.compareWithBaseline(
results.detailed,
suiteConfig.baseline
);
}
// Generate recommendations
results.recommendations = await this.generateRecommendations(results);
// Cooldown phase
await this.cooldown(suiteConfig.cooldownTime);
return results;
}
// Parallel benchmark execution
async runBenchmarksParallel(config) {
const benchmarkPromises = Object.entries(this.benchmarks).map(
async ([name, benchmark]) => {
const result = await this.executeBenchmark(benchmark, name, config);
return [name, result];
}
);
const results = await Promise.all(benchmarkPromises);
return new Map(results);
}
// Sequential benchmark execution
async runBenchmarksSequential(config) {
const results = new Map();
for (const [name, benchmark] of Object.entries(this.benchmarks)) {
const result = await this.executeBenchmark(benchmark, name, config);
results.set(name, result);
// Brief pause between benchmarks
await this.sleep(1000);
}
return results;
}
}
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 · 670 lines · 18 tokens per session scan A 41c15d830659
agent-benchmark-suite is a skill published in the GitHub repository proffesor-for-testing/agentic-qe (474 stars, last pushed 4d ago), licensed MIT. It adds 18 tokens to every session and 4,197 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to agent-benchmark-suite, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
foundry-config-setup
Resolve missing setup caused by a hardcoded Foundry project endpoint or model in a sample. Use when a sample fails because it uses a placeholder/hardcoded projectendpoint (for example "https://your-project.services.ai.azure.com") or a hardcoded model instead of reading them from the environment.
dogfood
Systematically explore and test a mobile app on iOS/Android with agent-device to find bugs, UX issues, and other problems. Use when asked to dogfood, QA, exploratory test, find issues, bug hunt, or test this app on mobile.
tooluniverse-drug-research
Comprehensive drug profiling — mechanism, primary/secondary targets, drug interactions, clinical-trial status, adverse events (FAERS), pharmacogenomics, and approval history. Use for full drug investigation reports, 'tell me about drug X' queries, and assembling drug profiles for clinicians, researchers, or regulatory…
monorepo-management
Master monorepo management with Turborepo, Nx, and pnpm workspaces to build efficient, scalable multi-package repositories with optimized builds and dependency management. Use when setting up monorepos, optimizing builds, or managing shared dependencies.
gh-bulk-issues
Orchestrate parallel Mastra Code headless instances to debug and fix multiple GitHub issues simultaneously.
qa-investigation
Investigate a specific test failure to its root cause and document the why. Detects whether a failing test is flaky (intermittent) or a deterministic bug during reproduction. Use when a test fails and you need the real cause, not just to make it green. Execution layer, not strategy review. Keywords: flaky test…