Skip to content
Open
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
1 change: 1 addition & 0 deletions docs/README.instructions.md
Original file line number Diff line number Diff line change
Expand Up @@ -174,6 +174,7 @@ See [CONTRIBUTING.md](../CONTRIBUTING.md#adding-instructions) for guidelines on
| [Quarkus MCP Server](../instructions/quarkus-mcp-server-sse.instructions.md)<br />[![Install in VS Code](https://img.shields.io/badge/VS_Code-Install-0098FF?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/instructions?url=vscode%3Achat-instructions%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Finstructions%2Fquarkus-mcp-server-sse.instructions.md)<br />[![Install in VS Code Insiders](https://img.shields.io/badge/VS_Code_Insiders-Install-24bfa5?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/instructions?url=vscode-insiders%3Achat-instructions%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Finstructions%2Fquarkus-mcp-server-sse.instructions.md) | Quarkus and MCP Server with HTTP SSE transport development standards and instructions |
| [R Programming Language Instructions](../instructions/r.instructions.md)<br />[![Install in VS Code](https://img.shields.io/badge/VS_Code-Install-0098FF?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/instructions?url=vscode%3Achat-instructions%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Finstructions%2Fr.instructions.md)<br />[![Install in VS Code Insiders](https://img.shields.io/badge/VS_Code_Insiders-Install-24bfa5?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/instructions?url=vscode-insiders%3Achat-instructions%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Finstructions%2Fr.instructions.md) | R language and document formats (R, Rmd, Quarto): coding standards and Copilot guidance for idiomatic, safe, and consistent code generation. |
| [React Controls & Platform Libraries](../instructions/pcf-react-platform-libraries.instructions.md)<br />[![Install in VS Code](https://img.shields.io/badge/VS_Code-Install-0098FF?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/instructions?url=vscode%3Achat-instructions%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Finstructions%2Fpcf-react-platform-libraries.instructions.md)<br />[![Install in VS Code Insiders](https://img.shields.io/badge/VS_Code_Insiders-Install-24bfa5?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/instructions?url=vscode-insiders%3Achat-instructions%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Finstructions%2Fpcf-react-platform-libraries.instructions.md) | React controls and platform libraries for PCF components |
| [Research Experiment Discipline](../instructions/research-experiment-discipline.instructions.md)<br />[![Install in VS Code](https://img.shields.io/badge/VS_Code-Install-0098FF?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/instructions?url=vscode%3Achat-instructions%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Finstructions%2Fresearch-experiment-discipline.instructions.md)<br />[![Install in VS Code Insiders](https://img.shields.io/badge/VS_Code_Insiders-Install-24bfa5?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/instructions?url=vscode-insiders%3Achat-instructions%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Finstructions%2Fresearch-experiment-discipline.instructions.md) | Discipline for research and experiment code: score null models first, keep calibration and held-out data physically separate, reproduce a published baseline before claiming improvements, report gains with paired error bars, and verify every guard by deliberately breaking it. Apply when writing evaluation harnesses, benchmark sweeps, or any code that reports a performance number. |
| [Ruby MCP Server Development Guidelines](../instructions/ruby-mcp-server.instructions.md)<br />[![Install in VS Code](https://img.shields.io/badge/VS_Code-Install-0098FF?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/instructions?url=vscode%3Achat-instructions%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Finstructions%2Fruby-mcp-server.instructions.md)<br />[![Install in VS Code Insiders](https://img.shields.io/badge/VS_Code_Insiders-Install-24bfa5?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/instructions?url=vscode-insiders%3Achat-instructions%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Finstructions%2Fruby-mcp-server.instructions.md) | Best practices and patterns for building Model Context Protocol (MCP) servers in Ruby using the official MCP Ruby SDK gem. |
| [Ruby on Rails](../instructions/ruby-on-rails.instructions.md)<br />[![Install in VS Code](https://img.shields.io/badge/VS_Code-Install-0098FF?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/instructions?url=vscode%3Achat-instructions%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Finstructions%2Fruby-on-rails.instructions.md)<br />[![Install in VS Code Insiders](https://img.shields.io/badge/VS_Code_Insiders-Install-24bfa5?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/instructions?url=vscode-insiders%3Achat-instructions%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Finstructions%2Fruby-on-rails.instructions.md) | Ruby on Rails coding conventions and guidelines |
| [Rust Coding Conventions and Best Practices](../instructions/rust.instructions.md)<br />[![Install in VS Code](https://img.shields.io/badge/VS_Code-Install-0098FF?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/instructions?url=vscode%3Achat-instructions%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Finstructions%2Frust.instructions.md)<br />[![Install in VS Code Insiders](https://img.shields.io/badge/VS_Code_Insiders-Install-24bfa5?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/instructions?url=vscode-insiders%3Achat-instructions%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Finstructions%2Frust.instructions.md) | Rust programming language coding conventions and best practices |
Expand Down
57 changes: 57 additions & 0 deletions instructions/research-experiment-discipline.instructions.md
Original file line number Diff line number Diff line change
@@ -0,0 +1,57 @@
---
description: 'Discipline for research and experiment code: score null models first, keep calibration and held-out data physically separate, reproduce a published baseline before claiming improvements, report gains with paired error bars, and verify every guard by deliberately breaking it. Apply when writing evaluation harnesses, benchmark sweeps, or any code that reports a performance number.'
applyTo: '**'
---

# Research Experiment Discipline

In research code the failure mode is rarely a crash; it is a number that
looks great and is wrong. These instructions make evaluation code hard to
fool - starting with its own author.

## Scoring and evaluation

- Route all method scoring through a single evaluation entry point module;
never compute metrics inline in experiment scripts.
- Score null-model baselines first (constant output, untrained model, input
copy). A well-scoring null model means the harness is broken: stop and fix
it before evaluating anything else.
- Keep one positive control - a signal the pipeline must detect. If it stops
detecting it, freeze conclusions; every null result since is unusable.
- Pin the metric convention (data range, averaging order, aggregation) in
one place. If a published convention differs from yours, report both,
labelled.

## Data separation

- Calibration/tuning data and evaluation data live in different files and
are loaded by different code paths; hyperparameter tuning reads
calibration data only.
- Split on the unit of independence (patient, user, site, time period), not
on files - two records from the same entity in different splits is group
leakage, and it inflates cross-validated gains.
- Budget accesses to the evaluation set; keep one final untouched split that
is scored exactly once for the headline number.

## Baselines and claims

- Reproduce at least one published baseline number before trusting your own.
A baseline you cannot match means the recipe has unread layers (optimizer,
loss, metric convention, operator) - do not "improve" an unmatched
baseline.
- A gain that does not reproduce on held-out data is not reported.
- Report confirmed gains as paired differences with an interval across
instances or seeds; a sub-point gain whose interval crosses zero is noise,
not a result.
- Persist numbers to files and commit them before quoting them in text.

## Guards and tests

- Algorithm implementations exist exactly once, in a module; experiment
scripts import them, never re-implement inline.
- Every new check or test must be demonstrated to fail on a deliberately
broken input before it counts - and fail for the right reason, not because
an unrelated assertion tripped first.
- When a hyperparameter sweep looks flat, measure the gradient force balance
between loss terms before concluding the parameter is inert; a flat sweep
often means every tested value sat on one side of the balance point.
Loading