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Found 4,129 Skills
CodeRabbit CLI local code reviews and .coderabbit.yaml configuration. Run AI reviews on uncommitted/committed changes before pushing or opening a PR, parse --agent findings, iterate fix-and-verify loops within hourly rate limits, and tune repo config for low-noise high-signal reviews. Use when reviewing local changes pre-push/pre-PR, installing or driving the coderabbit/cr CLI, creating or tuning .coderabbit.yaml, or reducing CodeRabbit review noise. Not for PR-side review loops and thread handling (git-pr), commits (git-commit), or CI status (git-ci)
Use when an agent is asked "what did I (or my team) work on yesterday / this week / today" across provider data in a relayfile mount (Linear, GitHub, Notion, Slack, Confluence, Jira, etc.). Tells the agent to consult the pre-computed `digests/yesterday.md` (and sibling digest files) at the workspace root BEFORE doing manual exploration with `ls`/`grep`/`find`. The digest is deterministic, exhaustive over the window, and costs one file read instead of dozens of provider queries.
Guidance for detection engineering in Microsoft Sentinel — building, testing, deploying, and maintaining analytics rules, hunting queries, and SOAR automation. Covers the Content Hub solution model, MITRE ATT&CK mapping, scheduled vs near-real-time (NRT) vs Fusion vs anomalies analytics, KQL detection patterns (joins, summarize, bin, materialize), entity mapping and incident enrichment, custom detections from Defender XDR vs Sentinel-only, automation rules, playbooks (Logic Apps), watchlists, threat intel matching, content as code with Azure DevOps / GitHub repositories integration, and detection lifecycle (validate → tune → version). WHEN: Sentinel analytics rule, KQL detection, MITRE mapping, Sentinel content hub, scheduled analytics, NRT rule, hunting query, Sentinel automation rule, Logic App playbook, custom detection, repositories Sentinel CI/CD, detection-as-code, watchlist, threat intel matching analytics, fusion alerts, anomalies, incident enrichment, entity mapping. DO NOT USE for Sentinel architecture/onboarding (use sentinel), Defender XDR custom detections only (overlap—use the side that owns the data), or generic KQL training.
Deploy browser games to here.now (default), GitHub Pages, or other hosting. Use when deploying a game, setting up hosting, or publishing a game build. Do NOT use for local development servers (use npm run dev).
Create video compositions, animations, title cards, overlays, captions, voiceovers, audio-reactive visuals, and scene transitions in FrameVideo HTML. Use when asked to build any HTML-based video content, add captions or subtitles synced to audio, generate text-to-speech narration, create audio-reactive animation (beat sync, glow, pulse driven by music), add animated text highlighting (marker sweeps, hand-drawn circles, burst lines, scribble, sketchout), or add transitions between scenes (crossfades, wipes, reveals, shader transitions). Covers composition authoring, timing, media, and the full video production workflow. For dev-loop CLI commands (init, lint, inspect, preview, render) see the framevideo-cli skill; for asset preprocessing commands (tts, transcribe, remove-background) see the framevideo-media skill; for Chanjing digital humans, OAuth, and website-project synthesis see the chanjing-digital-human skill.
Explore a codebase to find opportunities for architectural improvement, focusing on making the codebase more testable by deepening shallow modules. Use when user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more AI-navigable.
Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes — Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/PRD asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to "review since X".
Ultra-compressed commit message generator. Cuts noise from commit messages while preserving intent and reasoning. Conventional Commits format. Subject ≤50 chars, body only when "why" isn't obvious. Use when user says "write a commit", "commit message", "generate commit", "/commit", or invokes /caveman-commit. Auto-triggers when staging changes.
Create exercise directory structures with sections, problems, solutions, and explainers that pass linting. Use when user wants to scaffold exercises, create exercise stubs, or set up a new course section.
Use this skill when user wants to create a refactor plan.
Use when completing tasks, implementing major features, or before merging to verify work meets requirements
Use when you have a written implementation plan to execute in a separate session with review checkpoints