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.

Ir para a instalação Revisar arquivos

Repositório: zjunlp/DataMind
Última atividade na origem: 5 de julho de 2026 às 09:13
Idioma detectado do SKILL.md: inglês
Estrelas: 152
Forks: 13

Opções de instalação

Por padrão, está selecionado o prompt que primeiro revisa a origem. Você pode mudar para um comando direto ou baixar uma cópia local.

Instalar com um assistente de IA

Copie este prompt para o assistente de IA que você usa.

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/1/iter1/Average_Fee_Estimation.

Um comando direto ignora o prompt de revisão. Verifique a origem antes de executá-lo.

npx skills add https://github.com/zjunlp/DataMind --skill average-fee-estimation

O comando permanece em uma só linha. Role horizontalmente para revisá-lo antes de copiar.

Prefere uma cópia local? Baixe os arquivos disponíveis atualmente no SkillsMP.

Revise os arquivos de origem

Leia o SKILL.md e os arquivos complementares exibidos pelo SkillsMP antes de decidir se vai instalar.

SKILL.md

Instruções da origem · Visualização somente leitura

name	average-fee-estimation
description	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.

Voltar à pesquisa Voltar à instalação

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

2026-07-05

Ver todas deste repositório

average-fee-estimation

Informações da origem

Opções de instalação

Instalar com um assistente de IA

Revise os arquivos de origem

Mais deste repositório

Instalar com um assistente de IA

Mais deste repositório