Build .NET AI agents and multi-agent workflows with Microsoft Agent Framework using the right agent type, threads, tools, workflows, hosting protocols, and enterprise guardrails.
managedcode/dotPilot
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Skills in this repository
Showing 20 of 20 collected skills.
Build provider-agnostic .NET AI integrations with `Microsoft.Extensions.AI`, `IChatClient`, embeddings, middleware, structured output, vector search, and evaluation.
Use the Microsoft.Extensions stack correctly across Generic Host, dependency injection, configuration, logging, options, HttpClientFactory, and other shared infrastructure patterns.
Build or review distributed .NET applications with Orleans grains, silos, persistence, streaming, reminders, placement, testing, and cloud-native hosting.
Shape delivery workflow around backlog quality, roles, ceremonies, and engineering feedback. Use when defining how the team plans, tracks work, and turns feedback into durable improvements.
Create or update `docs/Architecture.md` as the global architecture map for a solution. Use when bootstrapping a repo, onboarding, or changing modules, boundaries, or contracts. Keep it navigational and use `references/overview-template.md` for scaffolding.
Design or refine CI/CD workflows, quality gates, release flow, and safe AI-assisted pipeline authoring. Use when adding or changing build pipelines, release stages, IaC-driven environments, or deployment rollback policy.
Prepare for, perform, or tighten code review workflow: PR scope, review checklist, reviewer expectations, and merge hygiene. Use when shaping pull requests, defining review policy, or auditing whether a change is review-ready.
Improve developer experience for multi-component solutions: onboarding, F5 contract, cross-platform tasks, local inner loop, and reproducible setup. Use when the repo is hard to run, debug, test, or onboard into.
Create or update a feature spec under `docs/Features/` with business rules, user flows, system behaviour, verification, and Definition of Done. Use when the user asks for a feature spec, executable requirements, acceptance criteria, behaviour documentation,…
Plan a human review for a large AI-generated code drop by reading the target area, tracing the natural user and system flows, identifying the riskiest boundaries, and prioritizing the files a human should inspect first. Use when the codebase is too large to…
Apply ML/AI project delivery guidance for data exploration, feasibility, experimentation, testing, responsible AI, and operating ML systems. Use when the repo includes model training, inference, data science workflows, or ML-specific delivery planning.
Capture or refine non-functional requirements such as accessibility, reliability, scalability, maintainability, performance, and compliance. Use when a feature or architecture change needs explicit quality attributes and trade-offs.
Design or improve observability for application and delivery flows: logs, metrics, traces, correlation, alerts, and operational diagnostics. Use when a change affects runtime visibility, failure diagnosis, SLOs, or alerting.
Apply baseline engineering security guidance: secrets handling, secure defaults, threat modelling references, and review checkpoints for auth, data flow, pipelines, and external integrations. Use when a change has security impact but does not require a full…
Apply SOLID, SRP, cohesion, composition-over-inheritance, and small-file discipline to code changes. Use when refactoring large files or classes, setting maintainability limits in `AGENTS.md`, documenting justified exceptions, or reviewing design quality.
Set up or refine solution-level governance for MCAF repositories: root and project-local `AGENTS.md`, rule precedence, solution topology, skill routing, and maintainability-limit policy placement. Use when bootstrapping a repo, restructuring a multi-project…
Set or refine source-control policy for repository structure, branch naming, merge strategy, commit hygiene, and secrets-in-git discipline. Use when bootstrapping a repo, tightening PR flow, or documenting branch and release policy.
Add or update automated tests for a change using the repository’s verification rules in `AGENTS.md`. Use when implementing a feature, bugfix, refactor, or regression test; prefer stable integration/API/UI coverage and pull deeper test strategy from the…
Use UI/UX engineering guidance for design systems, accessibility, front-end technology selection, and design-to-development collaboration. Use when bootstrapping a UI project, choosing front-end stack, or tightening design and accessibility practices.