average-transaction-value-stats

Skill for computing average transaction value statistics from payment transaction data in the dabstep dataset. Use this skill when a question asks about average transaction amount/value grouped by a categorical field (e.g., shopper_interaction, issuing_country, acquirer_country, aci), possibly filtered by merchant, card scheme, and/or date range.

Jump to install Review files

Repository: zjunlp/DataMind
Last source activity: July 5, 2026 at 09:13
Detected SKILL.md language: English
Stars: 152
Forks: 13

Install options

The review-first prompt is selected by default. You can switch to a direct command or download a local copy.

Install with an AI assistant

Copy this prompt into the AI assistant you're using.

Follow https://skillsmp.com/skill-install/prompt.md to install only the Agent Skill at https://github.com/zjunlp/DataMind/tree/main/datacope/reason_task/eval/skill/0/iter0/Average_Transaction_Value_Stats.

A direct command skips the review prompt. Inspect the source before running it.

npx skills add https://github.com/zjunlp/DataMind --skill average-transaction-value-stats

The command stays on one line. Scroll horizontally to inspect it before copying.

Prefer a local copy? Download the files currently available to SkillsMP.

Review the source files

Read SKILL.md and any companion files shown by SkillsMP before deciding whether to install.

SKILL.md

Source instructions · Read-only preview

name	average-transaction-value-stats
description	Skill for computing average transaction value statistics from payment transaction data in the dabstep dataset. Use this skill when a question asks about average transaction amount/value grouped by a categorical field (e.g., shopper_interaction, issuing_country, acquirer_country, aci), possibly filtered by merchant, card scheme, and/or date range.

Back to search Back to installation

longds-bench

Self-evaluate the current agent on LongDS-Bench (zjunlp/DataMind): the long-horizon, multi-turn agentic data-analysis benchmark. Use this when the user asks to run, score, or benchmark an agent on LongDS / LongDS-Bench / DataMind longds, or to measure multi-turn data-analysis ability. This does NOT use DSGym's Docker runtime — the agent running this skill IS the agent under test: it reads a locally-prepared dataset, performs the multi-turn analysis with its own tools, and is scored by the official LLM-judge rule. The ~19.5 GB dataset must be downloaded and prepared by the operator beforehand (see `$SKILL_DIR/../README`); this skill does not download it. Heavyweight and long-running; run in the background if supported and confirm scope first.

2026-09-06

applicable-fee-ids

Solve questions about which fee IDs apply to a payment merchant, transaction characteristics, or time period in the dabstep dataset. Use this skill for any question asking "which fee IDs apply to X", "what are the applicable fee IDs for merchant Y", "which merchants are affected by fee Z", or any query involving filtering fees.json based on payment characteristics or merchant attributes.

2026-07-05

average-fee-estimation

Solve dabstep Average_Fee_Estimation problems. Use this skill for questions asking about average payment processing fees, which card scheme is cheapest/most expensive in an average scenario, and fee calculations based on card scheme, account type, MCC description, credit/debit type, or any combination of these filters.

2026-07-05

View all from this repository

average-transaction-value-stats

Source facts

Install options

Install with an AI assistant

Review the source files

More from this repository

Install with an AI assistant

More from this repository