evaluation-reality-check

evaluation-reality-check is a skill for Codex from Emily2040/data-science-agent-skills. It costs 106 tokens per session (1,043 once invoked), scanned A, original, no licence file.

A data-science review workflow for designing model evaluations that reflect how and where a model will be used.

In plain words
What is it for?
Use it to plan evaluations, inspect evidence, classify decision risk, and document a reproducible testing approach.
Why use it?
It helps prevent misleading test results by considering the task, deployment setting, timing, groups of users or records, and consequences of errors.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit Use it to plan evaluations, inspect evidence, classify decision risk, and document a reproducible testing approach.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/emily2040/data-science-agent-skills/evaluation-reality-check
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 Emily2040/data-science-agent-skills --skill evaluation-reality-check
Clone the repo
git clone --depth 1 https://github.com/Emily2040/data-science-agent-skills

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 evaluation-reality-check

README.md
[![agentmods](https://agentmods.dev/badge/skills/emily2040/data-science-agent-skills/evaluation-reality-check/github.svg)](https://agentmods.dev/skills/emily2040/data-science-agent-skills/evaluation-reality-check)
Your own site
<a href="https://agentmods.dev/skills/emily2040/data-science-agent-skills/evaluation-reality-check"><img src="https://agentmods.dev/badge/skills/emily2040/data-science-agent-skills/evaluation-reality-check/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 evaluation-reality-check

Your own site · 80×15
<a href="https://agentmods.dev/skills/emily2040/data-science-agent-skills/evaluation-reality-check"><img src="https://agentmods.dev/badge/skills/emily2040/data-science-agent-skills/evaluation-reality-check.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 106 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,043 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 $0.00106 $0.01043
Opus 5 $0.00053 $0.00522
Sonnet 5 $0.00021 $0.00209
Haiku 4.5 $0.00011 $0.00104

Measured 12d ago against content hash f75b620f2a9a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

evaluation-reality-check 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 12d ago.

The scan reads SKILL.md. This mod also ships 3 executable files (scripts/checklist_score.py, scripts/quick_validate_skill.py, tests/test_skill_contract.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.

data-science-agent-skills/evaluation-reality-check/SKILL.md · 95 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

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. 12d ago First seen · 95 lines · 106 tokens per session scan A f75b620f2a9a

Subscribe to this mod's changes

evaluation-reality-check is a skill published in the GitHub repository Emily2040/data-science-agent-skills (16 stars, last pushed 3mo ago), with no licence file. It adds 106 tokens to every session and 1,043 once invoked, about $0.0005 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 2026-08-30.

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