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 duc01226/EasyPlatform --skill performance-testgit clone --depth 1 https://github.com/duc01226/EasyPlatformWrote 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/duc01226/easyplatform/performance-test)<a href="https://agentmods.dev/skills/duc01226/easyplatform/performance-test"><img src="https://agentmods.dev/badge/skills/duc01226/easyplatform/performance-test/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/duc01226/easyplatform/performance-test"><img src="https://agentmods.dev/badge/skills/duc01226/easyplatform/performance-test.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00058 | $0.04598 |
| Opus 5.5 | $0.00023 | $0.01839 |
| Sonnet 5.5 | $0.00012 | $0.00920 |
| Haiku 4.5 | $0.00006 | $0.00460 |
Grade A, and why
performance-test 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 — 169 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Codex compatibility note:
- Invoke
$skill-name: load the registered.agents/skills/<name>/SKILL.mdand execute it with Codex tools; no separateSkilltool or Claude mode switch is needed. Author.claude/**; mirrors are generated.- Track steps before execution and keep progress/evidence current. Explicit skill requests execute their protocol. Use the native question tool for required questions.
- Map foreign tool names to available host capabilities. A name mismatch needs no approval; an actually unavailable required capability stops with its step/evidence and a user question before adaptation.
- Subagent authorization: when a skill is user-invoked or AI-detected and its protocol requires subagents, that skill activation authorizes use of the required
spawn_agentsubagent(s) for that task.- Preserve protocol order unless the user approves a deviation. Workflows use
$start-workflow: gates stay fixed; other steps may flex with logged reasons and evidence.
Quick Summary
Goal: Build reusable, project-native performance tests and prove useful capacity under explicit data, workload and hardware limits.
Summary: Discover the project contract → research/bootstrap if needed → author realistic scenarios → static review/fix (two rounds maximum by default) → return AUTHORED. Only an explicit verification request continues to measurement/report analysis or the bounded green loop. Keep project preferences and honest evidence limits.
Key Rules:
- Define the workload/SLO and enforce the resource envelope before measuring; a user count alone proves no capacity.
- Write/init author only: no test execution, service startup, data seeding or smoke/load run. Automatically review/fix the authored artifacts statically, capped at two review rounds by default; offer verification through the host question tool afterward.
- Acceptance uses at least 100k rows per growable table and a 1,000-concurrent-user profile where applicable; smaller smoke runs prove only wiring.
- Green requires correctness, valid offered load, bounded memory/no observed OOM, query/search access-path evidence and recovery. Missing required evidence blocks PASS; preserve targets during repairs.
Workflow: Select mode/authority → discover → initialize if needed → author/static review → AUTHORED and optional verification offer; explicit verify/green → measure/analyze → bounded repair when requested → report.
What ships with it
4 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 · 169 lines · 58 tokens per session scan A d531155d80e0
performance-test is a skill published in the GitHub repository duc01226/EasyPlatform (12 stars, last pushed yesterday), licensed MIT. It adds 58 tokens to every session and 4,598 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-10-18.
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