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/int2t05/engineering-skills/load-testingnpx skills add int2t05/engineering-skills --skill load-testinggit clone --depth 1 https://github.com/int2t05/engineering-skillsWrote 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/int2t05/engineering-skills/load-testing)<a href="https://agentmods.dev/skills/int2t05/engineering-skills/load-testing"><img src="https://agentmods.dev/badge/skills/int2t05/engineering-skills/load-testing.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 | $0.00065 | $0.01483 |
| Opus 5 | $0.00032 | $0.00741 |
| Sonnet 5 | $0.00013 | $0.00297 |
| Haiku 4.5 | $0.00006 | $0.00148 |
Grade A, and why
load-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 3d 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 — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Load Testing
performance fixes measured slowness after it appears. Load testing finds the breaking point
before users do — generate realistic and adversarial traffic, characterize how the system
saturates, and validate that autoscaling and capacity claims hold. This is proactive capacity
validation, a distinct discipline from reactive optimization.
When to use
- Before launch: validate the system handles expected and peak traffic
- After a major change: new endpoint, architecture shift, dependency swap, data growth
- Setting or validating SLOs (p99 latency, error rate under load)
- Validating autoscaling rules and capacity headroom
- Triggers on "load test", "stress test", "capacity", "k6", "Locust", "wrk", "压测", "压力测试", "容量测试"
Not for: fixing a known performance bottleneck (use performance); unit/integration/e2e
correctness tests (use tdd / api-testing / e2e-testing). Load testing answers "how much can
it handle," not "does it work" or "why is it slow."
Steps
1. Define capacity goals
State the targets before generating load — without them, a load test produces numbers without judgment. Extract from SLOs, business expectations, or historical peak:
- Expected steady-state load (RPS, concurrent users)
- Peak load (2–10× steady state, sustained for how long)
- Acceptable p99 latency and error rate under target load
- The "break" threshold: the point past which the system is considered failed
Verify: goals are written as numbers with units, not "should handle traffic."
2. Design realistic traffic profiles
Load is only meaningful if it resembles real usage. Model the traffic mix from production analytics or expected user journeys:
- Read/write ratio matching real usage (not 100% reads)
- Geo distribution and connection patterns (keep-alive, new connections)
- Think time / pacing between requests (humans don't hammer at max RPS)
- Payload variety: don't test only the smallest payload — include the 95th-percentile size
- Authentication and session lifecycle (don't skip login cost)
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago First seen · 125 lines · 65 tokens per session scan A e201b59c75d6
load-testing is a skill published in the GitHub repository int2t05/engineering-skills (3 stars, last pushed 15d ago), licensed MIT. It adds 65 tokens to every session and 1,483 once invoked, about $0.0003 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 2026-08-31.
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