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 niels-emmer/myace --skill reproducibility-standardsgit clone --depth 1 https://github.com/niels-emmer/myaceWrote 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/niels-emmer/myace/reproducibility-standards)<a href="https://agentmods.dev/skills/niels-emmer/myace/reproducibility-standards"><img src="https://agentmods.dev/badge/skills/niels-emmer/myace/reproducibility-standards/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/niels-emmer/myace/reproducibility-standards"><img src="https://agentmods.dev/badge/skills/niels-emmer/myace/reproducibility-standards.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 | $0.00027 | $0.00305 |
| Opus 5 | $0.00014 | $0.00152 |
| Sonnet 5 | $0.00005 | $0.00061 |
| Haiku 4.5 | $0.00003 | $0.00030 |
Grade A, and why
Reproducibility Standards 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 8d 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
Purpose
Make every result reproducible from source control + logged state alone.
When to use it
Setting up a new project, starting a new experiment, or preparing work for handoff.
Checklist
- Seed all random generators: numpy,
random, torch, tensorflow, and any other stochastic components. Log seeds. - Pin dependencies: use lockfiles (
requirements.txt,poetry.lock,conda-lock) — not loose version ranges. - Capture environment: Dockerfile or conda env.yml that reproduces the exact runtime.
- Version data: use DVC, hash-based manifests, or snapshot the exact dataset version used.
- Log transforms: every preprocessing step (scaling, encoding, imputation) must be logged and reproducible.
- Pipeline DAG: capture the full pipeline graph with input/output hashes per step.
Expected output
A project setup where git clone → install → run reproduces the same results, verified by comparing logged metrics.
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.
- 8d ago First seen · 29 lines · 27 tokens per session scan A 630f0f50383b
Reproducibility Standards is a skill published in the GitHub repository niels-emmer/myace (1 stars, last pushed 4d ago), licensed MIT. It adds 27 tokens to every session and 305 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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