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 vraj-ai/skills --skill test-tpsgit clone --depth 1 https://github.com/vraj-ai/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/vraj-ai/skills/test-tps)<a href="https://agentmods.dev/skills/vraj-ai/skills/test-tps"><img src="https://agentmods.dev/badge/skills/vraj-ai/skills/test-tps/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/vraj-ai/skills/test-tps"><img src="https://agentmods.dev/badge/skills/vraj-ai/skills/test-tps.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 | $0.00000 | $0.00311 |
| Opus 5.5 | $0.00000 | $0.00124 |
| Sonnet 5.5 | $0.00000 | $0.00062 |
| Haiku 4.5 | $0.00000 | $0.00031 |
Grade A, and why
test-tps 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 5d 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.
What it actually says
Test TPS
Benchmark selected Pi model. Invocation spends provider quota and may incur cost.
Run
Resolve this skill directory, then run:
node <skill-dir>/scripts/test-tps.mjs <arguments>
Defaults: PI_PROVIDER, PI_MODEL, current reasoning level, 3 measured runs, 1 warmup, 256 requested output tokens.
Report command output verbatim. Do not reinterpret N/A metrics. Prefill TPS is N/A unless provider telemetry exposes prompt-processing duration. TTFT is latency, not prefill duration. Requested output tokens are a prompt target because Pi's CLI exposes no generic per-request max-output flag.
Rules
- Use current selected provider/model unless arguments override them.
- Preserve failed-run messages.
- Never print credentials or auth files.
- For stable comparisons, keep provider, model, reasoning, prompt, run count, and output target identical.
What ships with it
1 file 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.
- 5d ago Changed · -43 tokens per session bd4462c88760
- 1mo ago First seen · 31 lines · 43 tokens per session scan A 4713b36743cb
test-tps is a skill published in the GitHub repository vraj-ai/skills (4 stars, last pushed 6d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 311 tokens. 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 2026-09-20.
Other skills, from other repositories
code-review-pi
Review code for quality, run linters, check test coverage, fix issues, and enforce gates. Save the final report to ./specs/issues/003-code-review-pi/PROMPT.md. Use before committing changes.
goal-test
A local experiment for testing a goal command that keeps an AI coding session working until a stated condition is judged complete. It uses a separate language model to evaluate the conversation after each assistant turn.
sample-plugin
Sample plugin demonstrating the Skills + Tools model. Includes a Python tool (greeting) and a TypeScript tool (calculator).
relational-database-design
Designs or reviews a relational database schema for a given domain. Covers table structure, normalization, indexes, constraints, and migration strategy. Invoked when the user asks to design a schema, review a database structure, or optimize a data model.
aitask-add-model
Register a known code-agent model in models .json, optionally promote it to default across config/seed/DEFAULTAGENTSTRING.
codex-prompting
Internal guidance the stereo:codex-rescue subagent uses to compose prompts for Codex CLI models (coding, review, diagnosis, research); the main session does not load it.