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Found 6,689 Skills
Build type-safe LLM applications with DSPy.rb — Ruby's programmatic prompt framework with signatures, modules, agents, and optimization. Use when implementing predictable AI features, creating LLM signatures and modules, configuring language model providers, building agent systems with tools, optimizing prompts, or testing LLM-powered functionality in Ruby applications.
A method for iteratively improving text instructions for agents (skills / slash commands / task prompts / CLAUDE.md sections / code generation prompts) by having unbiased executors run them, then evaluating from both perspectives (executor self-report + instruction-side metrics). Repeat until improvement plateaus. Use immediately after creating or significantly revising a prompt or skill, or when you suspect the reason an agent isn't behaving as expected is due to ambiguity in the instructions.
Generative ideation engine. Takes a domain, trend, question, or constraint and produces 15-30 novel possibilities — things that might be true, businesses that could exist, futures that could unfold. Spawns a team of 6 specialist agents — Signal Scout, Analogist, Inverter, Combinator, Contrarian, Futurist — who each generate ideas from a distinct creative angle. The lead cross-pollinates across agents, finds unexpected combinations, and ranks the output by novelty × plausibility. Use when the user says "brainstorm", "what could exist", "what's possible", "generate ideas", "what might be true", "possibilities", or presents a domain and wants divergent exploration rather than evaluation of a specific idea.
Extract conversation skeleton or error signals from a single session file at a given path. Invoked by session-research agents after they have selected which sessions to deep-dive — not intended for direct user queries.
MaxIQ platform help — AI-native revenue intelligence with EchoIQ conversation intelligence, InspectIQ pipeline visibility, ForecastIQ AI-driven forecasting, 9 AI agents (NoteTaker, Radar, Summarizer, Coach, Taskmaster, Watchdog, Forecaster, Revenue Planner, Deal Mapper), usage-based pricing (no per-seat), Salesforce/HubSpot CRM sync. Use when EchoIQ not capturing all meeting types, AI Coach scoring criteria not matching your sales process, CRM fields not auto-populating from calls, InspectIQ deal signals seem inaccurate, ForecastIQ predictions not matching reality, comparing MaxIQ vs Gong vs Clari for revenue intelligence, setting up AI Radar keyword tracking, or evaluating usage-based CI pricing vs per-seat alternatives. Do NOT use for designing outbound cadences (use /sales-cadence) or cross-platform coaching programs (use /sales-coaching).
BrandJet AI platform help — multi-channel outreach sequences, unified inbox, brand monitoring, AI visibility tracking, lead discovery, social listening, email warmup, Artemis AI agent, and integrations. Use when outreach sequences aren't getting replies, brand mentions going unnoticed, multi-channel sequences feel disjointed, unified inbox is overwhelming, or AI visibility scores are dropping. Do NOT use for designing cadence strategy (use /sales-cadence), cross-platform deliverability (use /sales-deliverability), social listening strategy (use /sales-social-listening), or enriching contacts (use /sales-enrich).
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).
Curates insights from reflections and critiques into CLAUDE.md using Agentic Context Engineering
Code review using the reviewer agent
each::sense is the intelligent layer for generative media. A unified AI agent that generates marketing assets, ads, product images, videos, and creative content. It knows all AI models and automatically selects the best one for your task. Use for any creative content generation request.
Generate HeyGen presenter videos via the v3 Video Agent pipeline — handles Frame Check (aspect ratio correction), prompt engineering, avatar resolution, and voice selection. Required for any HeyGen video generation. Replaces deprecated endpoints with v3. Use when: (1) generating any HeyGen video (via API or otherwise), (2) sending a personalized video message (outreach, update, announcement, pitch, knowledge), (3) creating a HeyGen presenter-led explainer, tutorial, or product demo with a human face, (4) "make a video of me saying...", "send a video to my leads", "record an update for my team", "create a video pitch", "make a loom-style message", "I want to appear in this video", "generate a HeyGen video", "make a talking head video". Accepts avatar_id from heygen-avatar for identity-first HeyGen videos, or uses a stock presenter. Returns video share URL + HeyGen session URL for iteration. Chain signal: when the user wants to create/design an avatar AND make a video in the same request, run heygen-avatar first, then return here. Conjunctions to watch: "and then", "and immediately", "first...then", "X and make a video", "design [presenter] and record" = always CHAIN. If the user provides a photo AND wants a video, route to heygen-avatar first. NOT for: avatar creation or identity setup (use heygen-avatar first), cinematic footage or b-roll without a presenter, translating videos, TTS-only, or streaming avatars.
This skill helps agents use Figma's use_figma MCP tool in the FigJam context. Can be used alongside figma-use which has foundational context for using the use_figma tool.