eeg-model-evaluation-leakage

eeg-model-evaluation-leakage is a skill for Codex from Drchronx/ai-agent-research-starter-kit. It costs 61 tokens per session (333 once invoked), scanned A, original, no licence file.

A review process for testing EEG and brain-computer-interface machine-learning models without accidentally letting test information influence training.

In plain words
What is it for?
Use it to plan subject- or session-based splits, nested cross-validation, permutation tests, confidence intervals, repeated runs, and checks for class imbalance.
Why use it?
It helps reveal overly optimistic results caused by data leakage, such as related trials or subjects appearing in both training and test data.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit Use it to plan subject- or session-based splits, nested cross-validation, permutation tests, confidence intervals, repeated runs, and checks for class imbalance.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/drchronx/ai-agent-research-starter-kit/eeg-model-evaluation-leakage
Install

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.

Any agent
npx skills add Drchronx/ai-agent-research-starter-kit --skill eeg-model-evaluation-leakage
Clone the repo
git clone --depth 1 https://github.com/Drchronx/ai-agent-research-starter-kit

Made for: Codex.

Wrote 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.

agentmods badge for eeg-model-evaluation-leakage

README.md
[![agentmods](https://agentmods.dev/badge/skills/drchronx/ai-agent-research-starter-kit/eeg-model-evaluation-leakage/github.svg)](https://agentmods.dev/skills/drchronx/ai-agent-research-starter-kit/eeg-model-evaluation-leakage)
Your own site
<a href="https://agentmods.dev/skills/drchronx/ai-agent-research-starter-kit/eeg-model-evaluation-leakage"><img src="https://agentmods.dev/badge/skills/drchronx/ai-agent-research-starter-kit/eeg-model-evaluation-leakage/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.

agentmods 80×15 button for eeg-model-evaluation-leakage

Your own site · 80×15
<a href="https://agentmods.dev/skills/drchronx/ai-agent-research-starter-kit/eeg-model-evaluation-leakage"><img src="https://agentmods.dev/badge/skills/drchronx/ai-agent-research-starter-kit/eeg-model-evaluation-leakage.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 61 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 333 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00061 $0.00333
Opus 5 $0.00030 $0.00167
Sonnet 5 $0.00012 $0.00067
Haiku 4.5 $0.00006 $0.00033

Measured 8d ago against content hash 08a748f2c1ba, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

eeg-model-evaluation-leakage 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.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/create_bci_evaluation_audit.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

本地Skills功能分类库/15_BCI脑电智能建模Skills/eeg-model-evaluation-leakage/SKILL.md · 46 lines

The source is not reproduced here

A licence we could not identify

The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.

Read it on GitHub

Files

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.

Changes

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.

  1. 8d ago First seen · 46 lines · 61 tokens per session scan A 08a748f2c1ba

Subscribe to this mod's changes

eeg-model-evaluation-leakage is a skill published in the GitHub repository Drchronx/ai-agent-research-starter-kit (93 stars, last pushed 3mo ago), with no licence file. It adds 61 tokens to every session and 333 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 2026-09-03.

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