Sap Rpt1

Community

secondsky

sap-rpt1

SAP-RPT-1-OSS local tabular prediction workflows for FI/CO prototype datasets. Use when preparing SAP finance CSV exports for classification or regression experiments with source-verified setup, leakage checks, and governance review.

Overview

Publisher	secondsky
Repository	`sap-skills`
Skill name	`sap-rpt1`
Stars	445
Forks	117
Bundled files	10
License	GPL-3.0
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
10 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by secondsky on GitHub. Read the source before you install it.

Installation

Install the Sap Rpt1 AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/secondsky/sap-skills.git /tmp/sap-skills
mkdir -p .claude/skills
cp -r /tmp/sap-skills/plugins/sap-rpt1/skills/sap-rpt1 .claude/skills/sap-rpt1

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Sap Rpt1 in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Sap Rpt1 on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Sap Rpt1 is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

SAP-RPT-1-OSS FI/CO Predictor Skill

Use SAP-RPT-1-OSS for local, source-reviewed tabular prediction experiments on FI/CO CSV extracts. Keep this skill scoped to prototype and research workflows; do not present predictions as production finance, credit, audit, payment, or compliance decisions.

When to Use This Skill

Use this skill when preparing or reviewing SAP finance tabular data for local SAP-RPT-1-OSS experiments, especially:

FI-AR payment default or late-payment risk classification/regression.
FI-AP cash discount leakage or payment timing risk prediction.
FI-GL journal anomaly or unusual posting review prioritization.
Time-safe feature preparation, target leakage checks, and governance review for FI/CO CSV datasets.
Local SAP-RPT-1-OSS setup planning where Hugging Face access, Python 3.11, and GPU limits need to be explained before execution.

Do not use this skill as a hosted SAP-RPT API integration guide, production scoring service, SAP AI Core deployment guide, or live SAP extraction workflow.

Quick Start

Confirm the task is a local prototype using synthetic or approved masked FI/CO CSV data.
Read references/data-governance.md before touching real finance data.
Choose one prediction point and one target column. Define what was known at that point in time.
Select the Python executable from an approved Python 3.11 environment. On Windows this might be py -3.11 or .venv\Scripts\python.exe; on macOS/Linux this might be python3.11 or .venv/bin/python.
Use scripts/fico_data_prep.py --dry-run --input "<file.csv>" --target <column> to inspect schema and leakage risks.
Use scripts/rpt1_oss_predict.py --dry-run --input "<file.csv>" --target <column> to review local SAP-RPT-1-OSS prerequisites.
Add --encoding <encoding> or --delimiter ';' when enterprise CSV exports are not UTF-8 comma-delimited.
Run local inference only after explicit user request, Hugging Face access, license review, and an explicit output path or stdout mode.

FI/CO Use-Case Matrix

Detailed v1 recipes live in references/fico-use-cases.md.

Area	V1 depth	Typical target	First reference
FI-AR	Detailed	`paid_late`, `days_late`, `default_flag`	Payment default / late payment
FI-AP	Detailed	`discount_lost`, `discount_amount_lost`	Cash discount leakage
FI-GL	Detailed	`manual_review_flag`, `reversal_flag`, `outlier_flag`	Journal anomaly
CO/PS/CO-PA/FI	Starter only	Overrun, margin, cash, dispute, credit risk	Use-case matrix rows only

Data Preparation Patterns

Prefer source extracts already flattened to one row per prediction object, such as one invoice, one vendor invoice, one journal line, or one journal document. Rename technical SAP fields into semantic column names before inference; SAP-RPT-1-OSS uses column names and values as part of the tabular context.

Use S/4HANA starting points such as ACDOCA plus relevant master data and process extracts where available. Use ECC fallback tables only as starting points, not universal truth. Never assume table availability, field semantics, or release behavior without checking the target system.

Target Leakage Rules

Define the as-of date before selecting features. Exclude fields created or updated after that prediction point.

Common leakage examples:

Clearing date, clearing document, payment run result, or final payment status when predicting before payment.
Dunning, dispute, collection, write-off, or audit outcomes created after the prediction point.
Reversal or investigation flags created after a journal posting.
Actuals, settlements, or period-close adjustments posted after a forecast date.

Governance Checklist

Before using real FI/CO data, confirm business owner approval, legal/compliance approval, field minimization, masking of personal and bank-related data, time-based validation splits, documented target definitions, and human review. Use references/data-governance.md as the minimum checklist.

Do not use predictions as the sole basis for payment blocking, credit decisions, collections action, write-offs, audit conclusions, or control sign-off.

For Windows, macOS, Linux, and managed non-admin workstations, use references/enterprise-portability.md before suggesting setup or execution commands. Prefer user-writable virtual environments, approved cache locations, quoted paths, and explicit output locations.

Bundled Resources

references/source-review-2026-06-18.md: public source/model/product-page review and open upstream issue list.
references/fico-use-cases.md: detailed FI-AR, FI-AP, and FI-GL recipes plus starter matrix rows.
references/data-governance.md: minimum data governance and model-card checklist.
references/enterprise-portability.md: Windows, macOS, Linux, non-admin, proxy/cache, and CSV export guidance.
scripts/fico_data_prep.py: read-only CSV schema, target, and leakage inspection helper.
scripts/rpt1_oss_predict.py: opt-in local inference wrapper for SAP-RPT-1-OSS.
assets/*.csv: synthetic FI/CO sample datasets only.

Known Issues

Treat upstream SAP-RPT-1-OSS issues as source-reviewed limitations, not fixed behavior. See references/source-review-2026-06-18.md for issue numbers and titles reviewed from SAP-samples/sap-rpt-1-oss.

Local inference can download gated model artifacts, populate local caches, require Hugging Face authentication, and require substantial memory. Commands bundled with this plugin must not run inference directly.

Source and Verification Notes

Sources reviewed: SAP-samples sap-rpt-1-oss, Hugging Face SAP/sap-rpt-1-oss, and the SAP product page for SAP-RPT.

Verification scope is public source/model/product-page review only. Live SAP tenant validation, live SAP system validation, hosted SAP-RPT API validation, local inference benchmark validation, and production finance workflow validation were not performed.

Product boundary:

SAP-RPT-1-OSS is the local open model workflow documented here.
Hosted SAP-RPT-1 playground is product context only and is not bundled as a client.
SAP-RPT-1.5 is future product context from the 2026-06-18 source review and must not be described as currently available in this skill.

Related Skills

sap-ai-core: Use for SAP AI Core deployment and runtime architecture patterns.
sap-cloud-sdk-ai: Use for SAP Cloud SDK AI integration patterns and hosted AI service usage.
sap-hana-ml: Use for SAP HANA-native machine learning workflows.
sap-sqlscript: Use for SQLScript-based data extraction and feature preparation.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Sap Rpt1 AI skill do?

Why use Sap Rpt1 on TypingMind?

Because you install it once and use it with any model. Sap Rpt1 is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Sap Rpt1 in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/secondsky/sap-skills/tree/main/plugins/sap-rpt1/skills/sap-rpt1. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Sap Rpt1?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Sap Rpt1?

As many as you like. As long as a model supports skills, you can use Sap Rpt1 with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Sap Rpt1 AI skill free?

Yes. It is published on GitHub by secondsky under the GPL-3.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

SAP-RPT-1-OSS FI/CO Predictor Skill

When to Use This Skill

Quick Start

FI/CO Use-Case Matrix

Data Preparation Patterns

Target Leakage Rules

Governance Checklist

Bundled Resources

Known Issues

Source and Verification Notes

Related Skills

Bundled files

Frequently asked questions

Related AI Skills

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