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Found 1,203 Skills
Run a free 35B AI coding agent on Apple Silicon Macs using local LLMs via llama.cpp or MLX with web search, shell, and file tools.
Auto-Claude Graphiti memory system configuration and usage. Use when setting up memory persistence, configuring LLM/embedding providers, querying knowledge graph, or optimizing memory performance.
This skill should be used when the user asks to "fix the issues", "optimize existing content", "create new content for AI visibility", "run Morphiq Build", "generate schema markup", "create an llms.txt file", "run the content lab", or mentions building content fixes, generating schema, rewriting content for AI citations, or creating policy files. Consumes a Prioritized Roadmap (or user prompt, or existing content) and produces build artifacts through a 6-step content lab pipeline.
Implements and debugs browser Proofreader API integrations in JavaScript or TypeScript web apps. Use when adding Proofreader availability checks, monitored model downloads, proofread flows, correction metadata handling, or permissions-policy checks for built-in proofreading. Don't use for generic prompt engineering, server-side LLM SDKs, or cloud AI services.
Transition from static LLM chats to autonomous agents that execute multi-step tasks. Use this when you need to automate cross-platform reports (e.g., Snowflake to Google Docs), build self-service tools for non-technical teams, or create "anticipatory" engineering workflows that draft PRs based on Slack discussions.
Use Claude Code's full tool system with any OpenAI-compatible LLM — GPT-4o, DeepSeek, Gemini, Ollama, and 200+ models via environment variable configuration.
Used for answering, generating, refactoring, and troubleshooting code related to wot-ui v2. Keywords: wot-ui, uni-app, Vue3, wd-, ConfigProvider, useToast, useDialog, Form, Popup, theme, llms-full. Suitable for component selection, API query, sample page generation, theme customization, and troubleshooting common pitfalls.
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.
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).
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.
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.
Route AI coding queries to local LLMs in air-gapped networks. Integrates Serena MCP for semantic code understanding. Use when working offline, with local models (Ollama, LM Studio, Jan, OpenWebUI), or in secure/closed environments. Triggers on local LLM, Ollama, LM Studio, Jan, air-gapped, offline AI, Serena, local inference, closed network, model routing, defense network, secure coding.