Mark Wallace
48b6e2a44c
### Motivation and Context Replace `Skill` with `Plugin` in docs and dotnet readme's ### Contribution Checklist - [ ] The code builds clean without any errors or warnings - [ ] The PR follows the [SK Contribution Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md) and the [pre-submission formatting script](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md#development-scripts) raises no violations - [ ] All unit tests pass, and I have added new tests where possible - [ ] I didn't break anyone 😄 ## Summary This set of commits updates the terminology used in the project from SKILLS to PLUGINS. SKILLS have been renamed to PLUGINS throughout the codebase, and related documentation and comments have been updated accordingly. Additionally, the telemetry metrics have been updated to reflect the new naming convention. ## Changes - Rename SKILLS to PLUGINS throughout the codebase - Update related documentation and comments - Update telemetry metrics to reflect new naming convention --- *Powered by [Microsoft Semantic Kernel](https://github.com/microsoft/semantic-kernel)*
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Glossary ✍
To wrap your mind around the concepts we present throughout the kernel, here is a glossary of commonly used terms
Semantic Kernel (SK) - The orchestrator that fulfills a user's ASK with SK's available PLUGINS.
Ask - What a user requests to the Semantic Kernel to help achieve the user's goal.
- "We make ASKs to the SK"
Plugins - A domain-specific collection made available to the SK as a group of finely-tuned functions.
- "We have a PLUGIN for using Office better"
Function - A computational machine comprised of Semantic AI and/or native code that's available in a PLUGIN.
- "The Office PLUGIN has many FUNCTIONS"
Native Function - expressed with traditional computing language (C#, Python, Typescript) and easily integrates with SK
Semantic Function - expressed in natural language in a text file "skprompt.txt" using SK's Prompt Template language. Each semantic function is defined by a unique prompt template file, developed using modern prompt engineering techniques.
Memory - a collection of semantic knowledge, based on facts, events, documents, indexed with embeddings.
The kernel is designed to encourage function composition, allowing users to combine multiple functions (native and semantic) into a single pipeline.
