Average_Fee_Estimation

A guide for calculating and comparing average payment-processing fees in the dabstep dataset. It can use details such as card scheme, account type, merchant category, and credit or debit type.

In plain words
What is it for?
Use it to find average fees, compare which card schemes cost more or less, and calculate fees for selected transaction conditions.
Why use it?
It avoids working out fee calculations and comparisons from the raw payment data by hand.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/zjunlp/datamind/average_fee_estimation
Any agent
npx skills add zjunlp/DataMind --skill average_fee_estimation
Clone the repo
git clone --depth 1 https://github.com/zjunlp/DataMind

Made for: Claude Code, Codex.

Per session 69 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,336 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00069 $0.01336
Opus 5 $0.00034 $0.00668
Sonnet 5 $0.00014 $0.00267
Haiku 4.5 $0.00007 $0.00134

Measured 2d ago against content hash 768a06c2c302, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

Average_Fee_Estimation 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 2d 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.

datacope/general/docs/skills-example/Average_Fee_Estimation/SKILL.md · 116 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. 2d ago First seen · 116 lines · 69 tokens per session scan A 768a06c2c302

Subscribe to this mod's changes

Average_Fee_Estimation is a skill published in the GitHub repository zjunlp/DataMind (135 stars, last pushed 2d ago), with no licence file. It adds 69 tokens to every session and 1,336 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 2026-08-30.

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