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Found 1,148 Skills
Build and deploy GitHub Copilot SDK apps to Azure. USE FOR: build copilot app, create copilot app, copilot SDK, @github/copilot-sdk, scaffold copilot project, copilot-powered app, deploy copilot app, host on azure, azure model, BYOM, bring your own model, use my own model, azure openai model, DefaultAzureCredential, self-hosted model, copilot SDK service, chat app with copilot, copilot-sdk-service template, azd init copilot, CopilotClient, createSession, sendAndWait, GitHub Models API. DO NOT USE FOR: using Copilot (not building with it), Copilot Extensions, Azure Functions without Copilot, general web apps without copilot SDK, Foundry agent hosting (use microsoft-foundry skill), agent evaluation (use microsoft-foundry skill).
When the user wants to plan, evaluate, or build a free tool for marketing purposes — lead generation, SEO value, or brand awareness. Also use when the user mentions "engineering as marketing," "free tool," "marketing tool," "calculator," "generator," "interactive tool," "lead gen tool," "build a tool for leads," or "free resource." This skill bridges engineering and marketing — useful for founders and technical marketers.
Sub-skill for the intake phase of README-first AI repo reproduction. Use when the task is specifically to scan a repository, read README and common project files, extract documented commands, classify inference or evaluation or training candidates, and return a minimum trustworthy plan to the main skill. Do not use for environment setup, asset download, command execution, final reporting, paper lookup, or end-to-end orchestration.
Optional sub-skill for README-first AI repo reproduction. Use only when README and repository files leave a narrow reproduction-critical gap and the task is to resolve a specific paper detail such as dataset split, preprocessing, evaluation protocol, checkpoint mapping, or runtime assumption from primary paper sources while recording conflicts. Do not use for general paper summary, repo scanning, environment setup, command execution, title-only paper lookup, or replacing README guidance by default.
Sub-skill for the execution-evidence and reporting phase of README-first AI repo reproduction. Use when the task is specifically to capture or normalize evidence from the selected smoke test or documented inference or evaluation command and write standardized `repro_outputs/` files including patch notes when repository files changed. Do not use for initial repo intake, generic environment setup, paper lookup, target selection, or end-to-end orchestration by itself.
Use when encountering bugs or test failures - systematic debugging using debuggers, internet research, and agents to find root cause before fixing
Implement MVVM patterns using CommunityToolkit.Mvvm in Avalonia applications with ViewModels, Commands, and Dependency Injection
README-first AI repo reproduction orchestrator. Use when the user wants an end-to-end minimal trustworthy reproduction flow that reads the repo, selects the smallest documented inference or evaluation target, coordinates the intake, setup, execution, and optional paper-gap sub-skills, enforces conservative patch rules, and writes the standardized `repro_outputs/` bundle. Do not use for paper summary, generic environment setup, isolated repo scanning, standalone command execution, or broad research assistance outside repository-grounded reproduction.
Navigate difficult conversations and deliver constructive feedback using structured frameworks. Covers the Preparation-Delivery-Follow-up model and Situation-Behavior-Impact (SBI) feedback technique. Use when preparing for difficult conversations, giving feedback, or managing conflicts.
Retrieves biological sequences (DNA, RNA, protein) from NCBI and ENA with gene disambiguation, accession type handling, and comprehensive sequence profiles. Creates detailed reports with sequence metadata, cross-database references, and download options. Use when users need nucleotide sequences, protein sequences, genome data, or mention GenBank, RefSeq, EMBL accessions.
A skill to evaluate how secure Firestore security rules are. Use this when Firestore security rules are updated to ensure that the generated rules are extremely secure and robust.
Evaluate scientific claims and evidence quality. Use for assessing experimental design validity, identifying biases and confounders, applying evidence grading frameworks (GRADE, Cochrane Risk of Bias), or teaching critical analysis. Best for understanding evidence quality, identifying flaws. For formal peer review writing use peer-review.