Total 50,610 skills, AI & Machine Learning has 8484 skills
Showing 12 of 8484 skills
Audit token waste across agent systems (Claude Code, OpenClaw, Hermes, OpenCode). Detect idle burns, model misrouting, and config bloat with dollar savings.
Start a Ralph Loop for iterative self-referential development. Use when the user asks to run a ralph loop, start an iterative loop, or wants repeated autonomous iteration on a task until completion.
Authors and updates customization overrides for installed BMad skills. Use when the user says 'customize bmad', 'override a skill', 'change agent behavior', or 'customize a workflow'.
Disruptive innovation oracle for business model innovation and strategic disruption. Use when the user asks to talk to Victor or requests the Disruptive Innovation Oracle.
AI builders digest — monitors top AI builders on X and YouTube podcasts, remixes their content into digestible summaries. Use when the user wants AI industry insights, builder updates, or invokes /ai. No API keys or dependencies required — all content is fetched from a central feed.
Investigate Bedrock AgentCore runtime sessions via CloudWatch Logs Insights — resolve session/trace IDs, query OTEL spans, filter noise, build timelines. Use when debugging AgentCore agent sessions, tracing tool calls, or analyzing latency.
Create validated LLM-as-a-Judge evaluators following best practices — binary Pass/Fail judges with TPR/TNR validation for measuring specific failure modes. Use when you need to automate quality checks, build guardrails, or measure a specific failure mode identified during trace analysis. Do NOT use when failures are fixable with prompt changes (use optimize-prompt) or when failure modes are unknown (use analyze-trace-failures first).
Curate Claude Code's auto-memory into durable project knowledge. Analyze MEMORY.md for patterns, promote proven learnings to CLAUDE.md and .claude/rules/, extract recurring solutions into reusable skills. Use when: (1) reviewing what Claude has learned about your project, (2) graduating a pattern from notes to enforced rules, (3) turning a debugging solution into a skill, (4) checking memory health and capacity.
Low-latency streaming text-to-speech via OpenAI TTS API — adaptive sentence chunking, concurrent fetch pipelining, six voices.
Create AI influencer or branded character personas.
Score a single draft against the rubric. **Output only to the console, no file writing, no prediction**. Trigger phrases: "Score this [path]"/"score this [path]"/"Score this draft"/"Let's score first". It's a lightweight exploratory action before cheat-predict.
Find working Deepgram integration examples with third-party platforms and frameworks. Use whenever someone wants to integrate Deepgram with Twilio, LiveKit, LangChain, Vercel AI SDK, Discord, Vonage, Pipecat, Expo, FastAPI, Cloudflare Workers, Slack, Telegram, LlamaIndex, Zoom, Next.js, Nuxt, Django, SvelteKit, NestJS, Spring Boot, CrewAI, Riverside, SignalWire, and more. Examples are full runnable integration demos, not minimal feature snippets.