Manage stacked branches and pull requests with the gh-stack GitHub CLI extension. Use when the user wants to create, push, rebase, sync, navigate, or view stacks of dependent PRs. Triggers on tasks involving stacked diffs, dependent pull requests, branch chains, or incremental code review workflows.

Structured, risk-aware code review of a GitHub pull request using the gh CLI, with no-reference discovery of the current branch's PR, diff triage, unresolved-thread suppression, and severity-grouped findings ending in an approve/request-changes verdict.

Explains the ~/.worktrees/<path-key>/<branch> worktree convention, the dotfiles-repo opt-in, and what a dotfiles worktree cannot validate. Use to understand or explain worktree layout and its constraints; use the git-worktree skill to actually create, switch to, or delete one.

Use when implementation is complete and you need to decide how to integrate the work — presents structured options for merge, PR, keep, or discard

Design AI-IDE plugin marketplaces - requirements, host-specific payloads, local dogfood, release sync, and validation. Use when the user wants to create or publish a plugin marketplace.

Use when planning or synthesizing user research: choosing the method, deciding how many participants, or turning coded notes into insights. Runs study_designer.py, saturation_planner.py and insight_synthesizer.py, which refuses single-source insights.

Research competitor advertising strategies, keywords, ad copy, and landing pages. Use when the user asks about competitor PPC spend, keyword gaps, or wants to analyze competing brands.

Catalog and prioritize technical debt with a Lean/XP lens; top 5, quick wins, strategic debt. Use when the user asks for technical debt analysis, prioritization, quick wins, or tech debt payoff order.

Create Cursor rules for persistent AI guidance. Use when you want to create a rule, add coding standards, set up project conventions, configure file-specific patterns, create RULE.md files, or asks about .cursor/rules/ or AGENTS.md.

A Cursor Canvas is a live React app that the user can open beside the chat. You MUST use a canvas when the agent produces a standalone analytical artifact — quantitative analyses, billing investigations, security audits, architecture reviews, data-heavy content, timelines, charts, tables, interactive explorations, repeatable tools, or any response that benefits from visual layout. Especially prefer a canvas when presenting results from MCP tools (observability, analytics, issue-tracking and messaging tools) where the data is the deliverable — render it in a rich canvas rather than dumping it into a markdown table or code block. If you catch yourself about to write a markdown table, stop and use a canvas instead. You MUST also read this skill whenever you create, edit, or debug any .canvas.tsx file.

Archive existing wiki knowledge and rebuild from scratch, or restore from a previous archive. Use this skill when the user wants to start fresh, rebuild the wiki from all sources, archive current knowledge before a major change, or restore an older version. Triggers on "rebuild the wiki", "start over", "archive and rebuild", "restore from archive", "nuke and repave", "clean rebuild". Also use when the wiki has drifted too far from sources and incremental fixes won't cut it.

Enforce consistent tagging across the Obsidian wiki using a controlled vocabulary. Use this skill when the user says "fix my tags", "normalize tags", "clean up tags", "tag audit", "what tags should I use", "tag taxonomy", or whenever you're creating or updating wiki pages and need to choose the right tags. Also trigger when the user asks about tag conventions, wants to add a new tag to the taxonomy, or says "my tags are a mess". Always consult this skill's taxonomy file before assigning tags to any wiki page.

Use when the user wants agent-friendly vault artifacts or source ingest with text-first tools: Mermaid .mmd diagrams rendered with mmdc, Marp Markdown decks compiled to PDF/PPTX, Obsidian Excalidraw Markdown sketches, notebooklm-py summaries, yt-dlp talk metadata/captions, markitdown document conversion, or Makefile targets that wrap these workflows.

Apply Ponytail's reuse-first ladder when the user invokes /ponytail, asks for the simplest implementation, or wants to avoid over-engineering and new dependencies in a coding task. Preserve all requested behavior and required checks. Not a default for every coding task, a prose-compression mode, or a replacement for the repository's debugging, testing, or refactoring workflow.

Evaluate or integrate Headroom for large repetitive tool outputs, JSON, logs, or retrieved context. Use when the user names Headroom or asks to measure context compression in an application they control. Start with a local library trial; not a default proxy, provider switch, prose-shortening mode, or solution for an ordinary small command result.

Expertise in generating clean, correct, and efficient Dataform pipeline code for BigQuery ELT. Use this when creating or modifying Dataform pipelines, actions, or source declarations, when Dataform, SQLX, or BigQuery are mentioned in a transformation, when data needs to be ingested from GCS into BigQuery via Dataform, or when setting up a new Dataform project or configuring workflow_settings.yaml.

Set up a testing environment for RevenueCat purchases without charging real money. Use when the user says test RevenueCat purchases, sandbox setup, StoreKit configuration file, license tester, how do I test purchases without real money, set up sandbox account, internal testing track, or test paywall on iOS, Android, Kotlin Multiplatform, Flutter, or React Native.

Workflow required before any Mule application upgrade work. Call use_skill as your FIRST action — before reading project files (pom.xml, mule-artifact.json) or editing versions yourself — whenever the user asks to upgrade, migrate, bump, modernize, or move a Mule app to a newer Java version, a newer Mule Runtime version, or both. Covers upgrading Java and/or Mule Runtime, getting latest compatible connector versions, updating connector and plugin versions, and fixing impacts from operation changes in flows, DataWeave scripts, and MUnit tests. Even a targeted single-version bump like 'move this app to Java 17' or 'upgrade the runtime to 4.6' requires this workflow — do not hand-edit pom.xml versions and attempt the change yourself. When you call this skill, it must be the only tool call in that response.

Configure and implement Mule secure properties for encrypting sensitive data in Mule applications. Use this when the user wants to use/implement/add/configure Mule secure properties, secure configuration, or encrypt credentials in their Mule project.

Use Azure Advisor. WHEN: "show recommendations", "top Advisor actions", "prioritize recommendations", "service retirements", "update status". Unused-resource discovery and Cost/IdleResources requests use azure-advisor-cost-optimization; generic Cost and cross-category requests stay here. DO NOT USE FOR: fixes (use azure-advisor-actionability).