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Found 1,199 Skills
Supernormal platform help — AI agent for agencies that turns meeting context into deliverables (pitch decks, briefs, emails, spreadsheets). Use when setting up Supernormal desktop app for bot-free recording, Supernormal AI agents not generating deliverables, Supernormal credits running out or credit system confusion, Supernormal bot joining Zoom calls uninvited, comparing Supernormal to Sembly or Fathom or Fireflies for agency work, Supernormal MCP integration, Supernormal Slack or CRM sync to HubSpot or Salesforce, or Supernormal transcription accuracy issues with accents. Do NOT use for choosing between AI note-takers (use /sales-note-taker) or general meeting transcript API integration (use /sales-note-taker).
Audit design documents for missing decisions, compatibility risks, rollout gaps, and observability omissions. Use whenever the user asks to review a design doc, architecture proposal, implementation-facing design, plan, or design-adjacent markdown file for completeness, migration strategy, rollback, data handling, or suggested additions without directly editing the document. Also trigger on short requests such as `review <file>.md` or `audit <file>.md` when the target looks like a design, plan, architecture, proposal, or decision document.
Plan and build an RLM (Recursive Language Model) with predict-rlm. Interactively defines inputs, outputs, skills, and architecture from a goal, then implements the code. Use when the user wants to create a new RLM or explore whether one is feasible.
帮中文用户从当前已发布的 PostPlus skill surface 里找到合适技能，并给出公开安装命令。适合“有什么技能可以做 X”“我该装哪个技能”“帮我解释当前已发布技能范围”的场景。
Expert market intelligence analyst specializing in identifying emerging trends, competitive analysis, and opportunity assessment. Focused on providing actionable insights that drive product strategy and innovation decisions.
Expert in cultural systems, rituals, kinship, belief systems, and ethnographic method — builds culturally coherent societies that feel lived-in rather than invented
Builds production AI/ML systems — model training, fine-tuning, MLOps pipelines, model serving, evaluation frameworks, RAG optimization, and agent orchestration at scale. Use when the user asks to build, train, or deploy ML models, set up MLOps pipelines, optimize RAG systems, create inference endpoints, or design production AI agents.
Brain knowledge base operations. The core read/write cycle: brain-first lookup, read-enrich-write loop, source attribution, ambient enrichment, back-linking. Read this before any brain interaction.
Evaluates which SaaS tools can be replaced with AI agents. Takes a list of current SaaS subscriptions with costs, assesses replacement feasibility, estimates build vs buy economics, identifies Claude+MCP alternatives, and generates a comprehensive replacement plan with priority matrix, ROI analysis, implementation timeline, and risk assessment.
Work with the @upstash/box TypeScript/JavaScript SDK for sandboxed cloud containers with AI agents, shell, filesystem, and git. Use when building with Upstash Box, creating sandboxed environments, running AI agents in containers, or orchestrating parallel boxes.
A hybrid pattern where the system pauses execution to request human approval, input, or disambiguation before proceeding with critical actions. Use when user asks to "add human approval", "require human review", "human-in-the-loop", or mentions approval workflows, human oversight, or escalation.
Generate a cost report showing token usage and USD costs by agent and model