fast-pull-request
Generate a pull request description for the FAST repository using the provided template.
577 skills
Generate a pull request description for the FAST repository using the provided template.
Generate a feature request issue for the FAST repository using the provided template.
Generate a bug report issue for the FAST repository using the provided template.
Use Fabric CLI for Power BI operations — semantic models, reports, DAX queries, refresh, gateways. Activate when users work with Power BI items, need to refresh datasets, execute DAX, manage reports, or troubleshoot refresh failures.
Use Microsoft Fabric CLI (fab) to manage workspaces, semantic models, reports, notebooks, and Fabric resources. Activate when users mention fab, Fabric CLI, or need to automate Fabric operations.
Generate a Markdown triage report for open, non-draft pull requests in microsoft/ebpf-for-windows, including CI, freshness, sign-offs, and next-owner routing.
Perform a deep adversarial review of C/C++ changes between an active branch and a baseline branch in ebpf-for-windows. Produce both a detailed review report and a point-by-point fix list.
Best practices for HTTP client usage with Requests including sessions, error handling, and timeouts.
Best practices for numerical computing with NumPy including arrays, broadcasting, and vectorization.
Record-level CRUD and bulk operations — create, update, delete, upsert, CSV import, multi-table foreign-key loads, AI-generated sample data. Use when the user wants to write, modify, seed, or import data records into Dataverse tables.
Environment-level Dataverse administration — bulk delete, retention/archival, organization settings, OrgDB settings, recycle bin, audit, and the 37 allowlisted PPAC toggles. Use when the user wants to clean up data at scale, configure audit, change environment settings, manage retention policies, or list/cancel ERP batch jobs.
Discover connected data sources, add new data connectors through a user-confirmed form, inspect table metadata, and run bounded read-only probes when the current workspace data is insufficient.
The analyst's built-in capabilities: data-inspection tools and the always-available actions (visualize and ask_user).
Use this skill whenever the user asks to write, rewrite, humanise, de-AI, or polish prose so it doesn't read as AI-generated — or to review a draft for signs of AI writing. Apply it before returning any substantial prose the user will publish.
Analyze the user's communication style across their Teams chats and emails to build a reusable mimicry profile — greetings, tone, length, punctuation, sign-offs, common phrases, and quirks. Use this skill when the user asks to capture or analyze their writing style, or before configuring an assistant (e.g. an OOO auto-responder) that should write in their voice.
Use this skill any time SharePoint list is being fetched, searched, or shown to the user — whether it comes from a SharePoint/Microsoft 365 connector, a search result, a pasted export, or a fetched SharePoint URL. Apply it instead of dumping raw JSON or an ad hoc table whenever the user asks to "pull," "check," "look up," "find," or "show" anything from a SharePoint list, even if they never say the word "format.".
Use this skill whenever the user shares a Power BI or Analysis Services semantic model (a TMDL export, a BIM/JSON model definition, or a pasted list of tables, relationships, and measures) and asks for a model review, a performance check, or help fixing DAX, before writing or correcting any DAX measure for that model.
Trigger whenever the user uploads or references a Power Automate solution `.zip` and asks about references, dependencies on other flows, or related questions — phrasing like "document this flow", "what does this flow read/write/touch", "map the connection references", "audit this solution", or "which flows call which".
Use this skill when the user asks for a point of view, punchy line, positioning sentence, provocative statement, headline angle, opinion line, or concise strategic stance.
Scan the user's recent Microsoft 365 signals (emails, active chats/channels, calendar subjects) to surface recurring patterns worth productizing — either as a blog post (the user explains the same thing repeatedly) or as an automation (the user does the same multi-step task repeatedly). Use when the user asks "what should I write about?", "what could I automate?", "find patterns in my work", or invokes "/pattern-radar".
Analyze the user's own sent emails to build a personal writing-voice profile and generate a reusable personal voice skill from it. Use this skill whenever the user asks to analyze their writing style, learn their tone of voice, create/build/update a personal voice skill or "own voice" profile, make drafts "sound like me", or makes an equivalent request in any other language. Also use it when the user complains that generated emails or Teams messages don't sound like them and no personal voice skill exists yet.
Create, polish, rewrite, review, repurpose, brainstorm, or configure evidence-led LinkedIn posts, captions, comments, hooks, ideas, and conversation-scoped writing profiles from facts, notes, drafts, research, announcements, or lived experience. Use for the initial LinkedIn request and every follow-up clarification, revision, correction, constraint, or preference in the active task.
Required whenever a knowledge request names or implies a country, asks what applies "here," or compares countries. Treat Country as document metadata, not as a content-search term. Before any content search, general-knowledge answer, or clarification, use sharepoint_metadata_filter to discover and filter the Country column. Then pass every matching document URL to knowledge_search_sharepoint through scopeUrls.