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Found 657 Skills
Builds robust, tool-specific prompts from user intent using a structured extraction and routing engine. Use when the user asks for prompt creation, prompt repair, prompt decomposition, or adapting prompts across Claude, GPT, reasoning models, Gemini, coding IDEs, autonomous agents, and image tools.
The entry point for Intent, a UX and design strategy system. Sets project context, routes to specialized skills, and loads foundational UX knowledge. Activate when starting any UX or product design work, setting project context, routing to other skills, evaluating an existing product's UX, or when the user asks about design intent, user experience strategy, ethical design, dark patterns, or design systems thinking.
Use this skill when the user asks to "investigate incident", "triage this alert", "what's firing", "who got paged", "incident response", "check incident status", "SLO breaching", "error budget burned", "check service level", "SLI status", "who was notified", "check notification delivery", "verify alert routing", "MTTR", "incident severity", "error budget", "burn rate", "acknowledge incident", "resolve incident", "production incident", "what alerts are active", "incident timeline", "on-call triage", or wants to triage, manage, or respond to incidents using alerts, SLOs, and notifications.
Describe what an existing SigNoz alert rule does in plain language — the signal it watches, the threshold and evaluation behavior, the notification routing, and a one-line fire-frequency summary so the user knows whether the alert has been active. Make sure to use this skill whenever the user asks "what does this alert do", "explain alert X", "walk me through this rule", "how does my [Y] alert work", "is this alert configured correctly", or otherwise asks for an interpretation of an existing alert's configuration. Static explanation only — for diagnosing a specific firing incident, use `signoz-investigating-alerts`.
Domain expertise for Ai2 Asta MCP tools (Semantic Scholar corpus). Intent-to-tool routing, safe defaults, workflow patterns, and pitfall warnings for academic paper search, citation traversal, and author discovery.
Processes for routing community insights/actions and communicating outcomes back to members.
Use this skill for Obsidian-native formatting and derived artifacts such as Markdown formatting, wikilinks, registry tables, canvas files, optional Bases, CLI operations, and link repair. This skill does not decide knowledge routing.
Default entry point for any research request — a hybrid router that classifies the question deterministically and either delegates to a specialist research skill (pulse for trends/sentiment, grants for NIH funding, litreview for academic literature, syllabus for course reading, patent for prior-art + IP landscape, dossier for entity research) or runs its own plan-decompose-multi-source-search-synthesize-cite fallback workflow when no specialist matches. Always surfaces the routing decision so users can override. Triggers — "research [topic]", "look into [topic]", "what do we know about [topic]", "investigate [topic]", "find me information on [topic]", "do some research on [topic]", "I need to understand [topic]", or any research request that doesn't obviously match a more-specific specialist skill. Output is a markdown briefing (default) or .docx document (on request) with full citations and an audit log.
Connect to IDA databases and bootstrap sessions. Use when starting analysis, routing to other skills, or setting up CLI/HTTP/MCP connections.
Adopt Prisma Next into a new project, onto an existing database, or as the first move after a bootstrap tool dropped you into a scaffold. Use for "what can I do with Prisma Next", "what can I do next with Prisma", "where do I start", "what should I do first", "just ran createprisma", "createprisma", "npx createprisma", "npx create-prisma", "first steps", "first query", "I have a scaffolded Prisma Next project what now"; for `pnpm dlx prisma-next init` greenfield setup; and for `prisma-next contract infer` + `db sign` against an existing database. Also covers the connect-write-read first-arc orientation, the day-to-day commands (`contract emit`, `db init`, `db update`, `migration plan`, `migrate`, `db schema`, `db verify`), and routing to `prisma-next-contract` / `prisma-next-queries` / `prisma-next-runtime` for the next move. Flags: --target, --authoring, --schema-path, --probe-db, --output.
Performance optimization coordination playbook. Contains specialist routing table, TileIR two-step pipeline, kernel generation specialist selection, prioritization criteria, and safe modification workflow. Use when the user asks to apply optimizations, write kernels, or improve performance. Covers both user-specified optimization and autopilot-driven iterative optimization.
Debug Flask applications systematically with this comprehensive troubleshooting skill. Covers routing errors (404/405), Jinja2 template issues, application context problems, SQLAlchemy session management, blueprint registration failures, and circular import resolution. Provides structured four-phase debugging methodology with Flask-specific tools including Werkzeug debugger, Flask-DebugToolbar, and Flask shell for interactive investigation.