.NET MAUI is a C# and XAML framework for building native mobile and desktop applications from one shared codebase. Developers use it to create apps for Android, iOS, iPadOS, macOS, and Windows. The catalogue entries provide skills, instructions, and agents for working with .NET MAUI.
Borrowing it
Nothing to install: this file belongs to dotnet/maui. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/dotnet/maui/main/.github/skills/find-regression-risk/SKILL.mdgit clone --depth 1 https://github.com/dotnet/mauiWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/dotnet/maui/find-regression-risk)<a href="https://agentmods.dev/skills/dotnet/maui/find-regression-risk"><img src="https://agentmods.dev/badge/skills/dotnet/maui/find-regression-risk.svg" alt="Measured on agentmods" height="20"></a>- Snyk warn
- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00160 | $0.01197 |
| Opus 5 | $0.00080 | $0.00598 |
| Sonnet 5 | $0.00032 | $0.00239 |
| Haiku 4.5 | $0.00016 | $0.00120 |
Grade A, and why
find-regression-risk scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
find-regression-risk
Detects potential regression risks in a PR by cross-referencing removed lines against lines added by recent labeled bug-fix PRs.
How It Works
Purely mechanical — no AI/LLM. Five-step algorithm:
- PR diff — collects lines REMOVED by the PR under review.
- Git history —
git log --follow --since=6mofinds recent PRs that touched the same files. - Label filter — keeps PRs (or their linked issues) labeled
i/regression,t/bug,p/0, orp/1. - Fix diff — fetches each fix PR's diff and collects lines it ADDED to the same file.
- Compare — whitespace-insensitive string equality:
- 🔴 REVERT — removed line matches a line a fix PR added (highest risk).
- 🟡 OVERLAP — same file modified, but no exact line revert.
- 🟢 CLEAN — no bug-fix PRs touch the same files.
Standalone Invocation
# Analyze a specific PR (auto-detects files)
pwsh -NoProfile -Command '& ./.github/scripts/Find-RegressionRisks.ps1 -PRNumber 33908 -OutputDir /tmp/out'
# Analyze specific files only
pwsh -NoProfile -Command '& ./.github/scripts/Find-RegressionRisks.ps1 -PRNumber 33908 -OutputDir /tmp/out -FilePaths @("src/Core/src/Platform/Android/MauiWindowInsetListener.cs")'
Parameters
| Parameter | Required | Default | Description |
|---|---|---|---|
-PRNumber |
Yes | — | PR number to analyze |
-Repo |
No | dotnet/maui |
Repository in owner/name form |
-FilePaths |
No | auto-detect | Implementation files to check |
-MonthsBack |
No | 6 |
History window for git log |
-MaxRecentPRsPerFile |
No | 20 |
Rate-limit guard per file |
-BaseBranch |
No | main |
Base branch for git log scope |
-OutputDir |
No | — | Directory for output files |
-WriteInlineFindings |
No | off | Emit inline-findings.json |
Outputs
When -OutputDir is specified:
result.txt— single token:CLEAN,OVERLAP, orREVERTrisks.json— structured findings for downstream agentscontent.md— markdown summary for the PR commentinline-findings.json— (only with-WriteInlineFindings) inline annotations
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 90 lines · 160 tokens per session scan A db3fa84243f8
find-regression-risk is a skill published in the GitHub repository dotnet/maui (23,320 stars, last pushed today), licensed MIT. It adds 160 tokens to every session and 1,197 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
generate-code-cs
Generate the code from typespec for C#. Parameter: C# SDK repository root location .
build-sample-matrix
Build the matrix of all the samples throughout different frameworks.
translate-a-sample
Translate the Azure SDK sample from python to C# and generate markdownn file for the sample. Parameters: C# SDK repository root; python SDK repository root; Package name: one of Azure.AI.Projects, Azure.AI.Projects.Agents or Azure.AI.Extensions.OpenAI; The name of sample file in Python SDK repository.
author-test
Generate a test given sample. Parameters: C# SDK repository root; Package name: one of Azure.AI.Projects, Azure.AI.Projects.Agents or Azure.AI.Extensions.OpenAI; the sample to use as a starting point for the test.
update-changelog
Update the CHANGELOG.md files of C# projects. Parameters: csroot C# SDK repository root.
budget-checker
Validates that a proposed trip fits within the user's stated budget.