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Found 549 Skills
Invoke for ANY personal Bible devotion or scripture meditation request. This is a daily quiet time (QT) guide — use it whenever the user wants spiritual reflection on a Bible passage, NOT academic analysis. Common signals: asking for today's reading, wanting guided devotion, seeking stillness with scripture, mentioning a personal reading plan, or using terms like 靈修、靈糧、默想、嗎哪、 QT、quiet time、devotional. Even short or casual requests like just saying "QT" or "今天讀什麼" should trigger this skill. Delivers a first-century Jewish perspective devotional for mainstream Christians. Depends on bible-buddy skill. EXCLUDE: theological scholarship, academic exegesis, verse-by-verse analysis, sermon/teaching prep, translation comparison, comparative religion essays, or original-language research tasks — those belong to bible-buddy or bible-fact-check.
Sets up or repairs the AGENTS.md source-of-truth pattern for any project. Creates a well-structured AGENTS.md with real stack info auto-detected from the project, then wires all AI config satellites (.claude/CLAUDE.md, .github/copilot-instructions.md, .agents/rules/, MEMORY.md) to point to it. Eliminates duplication. Always runs in plan mode — asks before acting. Use this skill whenever the user mentions AGENTS.md, agent config, source of truth for AI rules, setting up Claude/Copilot/Cursor for a project, fixing duplicate AI instructions, or wants to consolidate AI configuration files. Trigger even if the user just says "set up agents" or "fix my AI config".
Apply consistent photo adjustments across a set of images so they look like they were edited together. Use this skill whenever the user says "make my photos look cohesive", "give all these the same style", "apply a warm and golden feel to all of these", "make this cinematic", "match the look across my photos", "edit all my travel photos the same way", "batch edit these", "make these consistent", "fix my phone photos", or uploads a folder of photos and wants a unified, polished result. Also triggers for requests like "apply a preset to all of these", "make these look professional", or "they were shot in mixed lighting — can you fix them all". Outputs direct final image URLs plus an in-chat preview grid and optional Firefly Board link. Access: 🔐 Signed-In required | Gen AI: ❌
Generates blog post thumbnail images for Orbitant following the brand's visual identity, using Google's Imagen API (Nano Banana 2). Activates when creating blog images, generating thumbnails, designing featured images for articles, or when someone needs a visual for an Orbitant insight/blog post. Use this skill even if the user just says "I need an image for this article", "create a thumbnail", "generate a hero image", or "make a featured image". Also triggers when the user mentions "Nano Banana 2", "image generation", or asks for a prompt for an AI image tool.
Delegate a sub-task to Gemini CLI via the Agent Client Protocol (ACP). Use this skill whenever you want to hand off work to Gemini — large-context summarization, Google Search grounding, tasks that exceed Claude's context window, or anything where Gemini's 1M-token window or real-time search gives an advantage. Also invoke when the user asks you to "ask Gemini", "check with Gemini", or "run this through Gemini". The script handles subprocess lifecycle and ACP session setup; you just provide the prompt and read stdout.
Use when the user asks "what can Cekura do", "what commands are available", "help me with Cekura", "what skills do I have", "show me Cekura features", "what's available", "how do I use Cekura", or needs guidance on which Cekura skill to use for their task. Also relevant as the entry point when a user has just installed cekura-skills for the first time.
Run the canonical NVIDIA AOI three-phase training pipeline — Phase 1 AutoML baseline (HPO), Phase 2 DEFT loop (RCA → SDG → mining → plain-train retrain), Phase 3 AutoML refinement on the DEFT-augmented dataset. This is the default entry point for any "run the AOI workflow", "fine-tune my PCB AOI model end-to-end", "improve my AOI ChangeNet model", or "AOI workflow with AutoML" request — route here instead of tao-run-deft-aoi directly unless the user explicitly asks for the DEFT loop ONLY (e.g. "run JUST the DEFT loop", "skip AutoML, only DEFT"). Also handles the same three-phase pattern for non-AOI DEFT applications — AutoML baseline then DEFT loop warm-started from AutoML's winning HPs then post-DEFT AutoML refinement on the iteration-augmented dataset. Trigger phrases include "run the AOI workflow", "AOI end-to-end", "AutoML + DEFT", "AutoML then DEFT", "tune hyperparameters then DEFT", "DEFT with AutoML at both ends", "warm-start DEFT", "improve my AOI model".
Link workspace packages in monorepos (npm, yarn, pnpm, bun). USE WHEN: (1) you just created or generated new packages and need to wire up their dependencies, (2) user imports from a sibling package and needs to add it as a dependency, (3) you get resolution errors for workspace packages (@org/*) like "cannot find module", "failed to resolve import", "TS2307", or "cannot resolve". DO NOT patch around with tsconfig paths or manual package.json edits - use the package manager's workspace commands to fix actual linking.
Visual feedback from humans via screenshot annotations. Use this skill CONSTANTLY — any time you need visual context, want to verify UI changes, need to confirm layout, debug a visual issue, check styling, validate a design, or show your work. Capture the screen, look at it, figure out what you need feedback on, annotate it, and ask. Do not ask the user what to capture — just capture and look.
Re-reads code you just wrote with fresh perspective to catch bugs, errors, and issues. Use after completing a feature, fixing a bug, or any code changes. Triggers on "review my code", "fresh eyes", "check for bugs", "did I miss anything", or "sanity check".
Automatically intercepts and optimizes prompts using the prompt-learning MCP server. Learns from performance over time via embedding-indexed history. Uses APE, OPRO, DSPy patterns. Activate on "optimize prompt", "improve this prompt", "prompt engineering", or ANY complex task request. Requires prompt-learning MCP server. NOT for simple questions (just answer them), NOT for direct commands (just execute them), NOT for conversational responses (no optimization needed).
Expert guidance for Google Ads Script development including AdsApp API, campaign management, ad groups, keywords, bidding strategies, performance reporting, budget management, automated rules, and optimization patterns. Use when automating Google Ads campaigns, managing keywords and bids, creating performance reports, implementing automated rules, optimizing ad spend, working with campaign budgets, monitoring quality scores, tracking conversions, pausing low-performing keywords, adjusting bids based on ROAS, or building Google Ads automation scripts. Covers campaign operations, keyword targeting, bid optimization, conversion tracking, error handling, and JavaScript-based automation in Google Ads editor.