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 MonumentalSystems/Atlas-Agent-Teams --skill performance-testinggit clone --depth 1 https://github.com/MonumentalSystems/Atlas-Agent-TeamsWrote 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/monumentalsystems/atlas-agent-teams/performance-testing)<a href="https://agentmods.dev/skills/monumentalsystems/atlas-agent-teams/performance-testing"><img src="https://agentmods.dev/badge/skills/monumentalsystems/atlas-agent-teams/performance-testing/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/monumentalsystems/atlas-agent-teams/performance-testing"><img src="https://agentmods.dev/badge/skills/monumentalsystems/atlas-agent-teams/performance-testing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00011 | $0.02238 |
| Opus 5 | $0.00005 | $0.01119 |
| Sonnet 5 | $0.00002 | $0.00448 |
| Haiku 4.5 | $0.00001 | $0.00224 |
Grade A, and why
performance-testing 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.
How it starts
The opening of the file, as written. The whole thing — 325 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Testing
Performance Testing Types
Load Testing
Purpose: Verify system performance under expected load
- Simulates expected user traffic and data volume
- Identifies performance bottlenecks under normal conditions
- Establishes performance baselines
- Validates SLA compliance
Key Metrics:
- Response time (average, median, p95, p99)
- Throughput (requests per second, transactions per second)
- Error rate
- Resource utilization (CPU, memory, disk, network)
Stress Testing
Purpose: Identify system breaking points
- Exceeds expected load to find limits
- Tests system recovery after failure
- Identifies failure modes and error handling
- Validates graceful degradation
Key Metrics:
- Maximum concurrent users before failure
- Maximum throughput before failure
- Time to recover after load reduction
- Error patterns and failure modes
Spike Testing
Purpose: Handle sudden traffic increases
- Simulates sudden traffic spikes (e.g., flash sales, viral content)
- Tests system elasticity and auto-scaling
- Validates queuing and throttling mechanisms
- Identifies race conditions under load
Key Metrics:
- Response time during spike
- Error rate during spike
- Time to stabilize after spike
- Queue depth and processing time
Soak Testing
Purpose: Verify stability over extended periods
- Runs sustained load for hours or days
- Identifies memory leaks and resource exhaustion
- Tests database connection pool stability
- Validates garbage collection efficiency
Key Metrics:
- Memory usage over time
- Response time trends
- Error rate over time
- Resource utilization trends
Volume Testing
Purpose: Test with large data volumes
- Tests performance with realistic data sizes
- Identifies database query performance issues
- Tests file system and storage performance
- Validates data migration performance
Key Metrics:
- Query execution time with large datasets
- Index usage and effectiveness
- Storage I/O performance
- Data processing throughput
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 · 325 lines · 11 tokens per session scan A 66121bf02a60
performance-testing is a skill published in the GitHub repository MonumentalSystems/Atlas-Agent-Teams (21 stars, last pushed 29d ago), licensed MIT. It adds 11 tokens to every session and 2,238 once invoked, about $0.0001 per session on Opus 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 2026-09-03.
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