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Found 1,573 Skills
Observe.AI platform help — enterprise contact center intelligence with Auto QA scoring on 100% of interactions, Agent Copilot real-time guidance, Coaching Copilot post-call performance management, VoiceAI and ChatAI virtual agents, screen recording, Insights Copilot. Use when setting up Observe.AI Auto QA scorecards for contact center agents, Agent Copilot not surfacing guidance during live calls, transcription accuracy issues or speaker attribution errors, comparing Observe.AI vs Balto or Cresta or CallMiner for contact center QA, integrating Observe.AI with Five9 or Amazon Connect or Talkdesk, or configuring compliance monitoring and regulatory audit trails. Do NOT use for building a general coaching program (use /sales-coaching) or reviewing a specific call transcript (use /sales-call-review).
Optimize content for AI search engines including Google AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and Microsoft Copilot. Covers generative engine optimization (GEO), AI citability audits, content structuring for extraction, schema markup, bot access configuration, and monitoring. Use when optimizing for AI search, AI overviews, generative search, LLM visibility, semantic search, entity optimization, or when user mentions AI SEO, GEO, Perplexity citations, ChatGPT visibility, or AI-generated answers.
This skill should be used when the user wants to run baseline evaluations on existing agent skills, regenerate transcripts after a model upgrade, or check whether a skill still solves the gap it was authored for. Common triggers include "rerun the baselines", "re-eval skill X", "test all the skills", "check for skill drift", and "run the evals". Bakes in verbatim transcript capture (no paraphrasing), deterministic-only grading (regex / contains / file_exists — no LLM-as-judge), and the iteration-N workspace convention. Skip when authoring a new skill (use skill-creator) or modifying skill content directly.
Pre-production audit that scans a codebase for security, database, deployment, code quality, AI/LLM, dependency, frontend, and observability issues. Intercepts deploy commands and blocks until critical items pass. Stack-agnostic. Use for "run ship gate", "am I ready to ship", "pre-launch audit", "can I deploy", "push to production", "go live checklist", "preflight check". Not for CI/CD setup or infra provisioning.
ALWAYS invoke this skill when the user mentions 10x-cli, @przeprogramowani/10x-cli, the 10xDevs CLI, or the 10xDevs course environment in a setup context. This skill fetches the live README — Claude does not know 10x-cli's current install steps without it. Applies to: installing, updating, reconfiguring for different AI tools (Cursor, Copilot, Claude Code), permission/npm errors, authentication, and onboarding after 10xDevs enrollment. Excludes: developing 10x-cli source code, contributing to the repo, building similar CLIs, or general project setup.
Guides digital forensics for security incidents—evidence acquisition and chain of custody, disk/memory/mobile/cloud artifact analysis, log and network forensics, timeline correlation, malware artifact triage, and investigation reports for legal/IR and expert-witness preparation outlines (not legal advice). Use when preserving and analyzing forensic artifacts, building super-timelines, documenting acquisition worksheets, triaging malware samples, or preparing forensic findings for counsel—not live incident command (incident-responder), SOC alert queue triage (soc-analyst), authorized penetration testing (penetration-tester), deep binary RE (reverse-engineer), LLM red team (ai-redteam), enterprise ISMS programs (information-security-engineer), audit control mapping (compliance-engineer), or cloud guardrail implementation (cloud-security-engineer).
Improve Coval trace quality after basic ingestion works. Use when traces are sparse, missing useful STT/LLM/TTS/tool spans, missing attributes needed for Coval built-in metrics, or when a customer wants maximum debugging and observability value from agent traces.
Use when launching cloud VMs, Kubernetes pods, or Slurm jobs for GPU/TPU/CPU workloads, training or fine-tuning models on cloud GPUs, deploying inference servers (vllm, TGI, etc.) with autoscaling, writing or debugging SkyPilot task YAML files, using spot/preemptible instances for cost savings, comparing GPU prices across clouds, managing compute across 25+ clouds, Kubernetes, Slurm, and on-prem clusters with failover between them, troubleshooting resource availability or SkyPilot errors, or optimizing cost and GPU availability.
Use this skill whenever the user asks about WWDC sessions, Apple Developer videos, WWDC transcripts, session IDs, technologies announced at WWDC, or wants an agent to find, compare, cite, summarize, or navigate WWDC session content. Fetch current docs from wwdc.ai via llms.txt and page markdown. Maintained by Superwall.com: the quickest way to add in-app subscriptions and paywalls to your app.
Voice agents represent the frontier of AI interaction - humans speaking naturally with AI systems. The challenge isn't just speech recognition and synthesis, it's achieving natural conversation flow with sub-800ms latency while handling interruptions, background noise, and emotional nuance. This skill covers two architectures: speech-to-speech (OpenAI Realtime API, lowest latency, most natural) and pipeline (STT→LLM→TTS, more control, easier to debug). Key insight: latency is the constraint. Hu
Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO) strategies for AI-powered search visibility in ChatGPT, Perplexity, Google AI Overviews, and other AI search platforms. Use when working with aeo, geo, ai search, chatgpt search, perplexity, ai overviews, generative search, llm visibility.
Strategic clinical trial design feasibility assessment using ToolUniverse. Evaluates patient population sizing, biomarker prevalence, endpoint selection, comparator analysis, safety monitoring, and regulatory pathways. Creates comprehensive feasibility reports with evidence grading, enrollment projections, and trial design recommendations. Use when planning Phase 1/2 trials, assessing trial feasibility, or designing biomarker-driven studies.