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Test CodexBar against real provider services, check application settings, and verify menu contents. Use command-line checks and visual evidence to distinguish authentication problems, API mismatches, and display issues before a release.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Checking provider connections before a release
• Investigating missing usage data or authentication failures
• Comparing menu contents with enabled providers

Retrieve current Chinese-language AI news from AIHOT to summarize daily or weekly developments, follow company and product announcements, and explain trending events. Access is anonymous and read-only, with no API key required.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Catching up on today’s major AI news
• Reviewing AI developments from the past week
• Following updates about a specific company, product, or model

Builds an Apigee proxy that inspects an agent’s model requests and responses through Google Cloud Agent Gateway. It measures token usage by model, identifies callers, and can add prompt screening or a cache for similar prompts.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Measure token usage by model
• Identify callers behind model requests
• Add Model Armor prompt screening

Guides migration of existing AI inference workloads to self-hosted GKE, Google’s managed Kubernetes service. Covers requirements, GPU sizing, deployment configuration, model storage, validation, and traffic cutover using gcloud and kubectl.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Migrating an existing Cloud Run AI service to GKE
• Planning a self-hosted replacement for Gemini API inference
• Sizing GPUs and preparing deployment configuration

Call Gemini and OpenMaaS models such as Llama, DeepSeek, and Qwen through Google Cloud Agent Platform. Prepare authentication and SDK code, run prompts, configure connection endpoints, and troubleshoot common request errors.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Send a test prompt to Gemini
• Call Llama or DeepSeek with the OpenAI SDK
• Write code to call an existing custom endpoint

Delegate coding, analysis, refactoring, or reviews from Claude Code to Codex CLI. The skill explains unattended execution, permission settings, output capture, parallel tasks, and independent checks of changed files and test results.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Delegate implementation while retaining planning responsibility
• Get a second opinion on code changes
• Split independent tasks across separate git worktrees

Import existing notes and agent instructions into LifeOS by splitting content into sections and proposing destinations. Review uncertain classifications, approve selected groups, and retain source information alongside the imported material.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Importing Obsidian or Notion exports into LifeOS
• Moving notes from an older LifeOS installation
• Reviewing and importing CLAUDE.md or Cursor rules

Create blog illustrations, technical diagrams, comparisons, comics, and icons through workflows tailored to each format. The skill guides composition, color, and model selection, then stages generated images for review before they are used in a project.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Creating blog header illustrations
• Explaining a system with a technical diagram
• Visualizing comparisons and timelines

Audit content for AI search by checking clear answers, supporting sources, author and brand information, and crawler access. Receive a readiness report with prioritized improvements and specific suggestions for rewriting passages.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing content for Google AI Overviews and other AI search
• Rewriting passages into clear, self-contained answers
• Checking crawler access for search and model training separately

Audit the technical factors that affect how search engines discover and index a website. Check crawl access, URLs, security, mobile pages, loading performance, and JavaScript rendering, then report measured results with prioritized fixes.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigate why pages are missing from search results
• Check technical SEO before a launch or site migration
• Review mobile content and page performance

Add DeepEval tracing to Python AI applications so execution steps appear in Confident AI. Choose a supported integration or manual @observe instrumentation, then capture inputs, outputs, step types, tags, and metadata.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Trace execution steps in a Python AI application
• Select tracing integrations for an existing framework
• Add manual tracing with @observe

Answer questions about videos from URLs or local files using timestamped visual and spoken evidence. Choose extracted frames and transcripts, or let Gemini view the full video with a configured API key.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Summarizing a video's visuals and speech
• Finding timestamps relevant to a question
• Checking a specific section of a long video

Review content for citation in AI search answers. Use checklists covering clear definitions, sourced data, author information, FAQs, and structured data, then plan how to monitor citations, brand mentions, and AI-referred traffic.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing articles for citation in AI search answers
• Organizing definitions, sources, and FAQs in content
• Checking author details and structured data

Prepare video clips with yt-dlp, whisper, and ffmpeg, covering downloads, speech transcription, subtitle files, trimming, and vertical formatting. Also includes methods for adding generated speech and sending finished videos through messaging APIs.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Turning longer videos into vertical clips
• Creating and embedding subtitles from speech
• Adding narration made with text-to-speech

Write and review launch prompts for agents working autonomously for hours or days. Define successful deliverables, excluded partial results, stopping rules, worker handoffs, and evidence-based review requirements so completion can be assessed against explicit criteria.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Turning vague requests into precise task briefs
• Defining stopping rules for long autonomous runs
• Specifying deliverables for parallel workers

Improve research code, results, and paper drafts through repeated review by a second Codex agent. The workflow implements fixes, checks them again, and records assessments and unresolved issues across up to four rounds.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Improve research before submitting a paper
• Repeat fixes and reviews of experimental results
• Track unresolved concerns across review rounds

Get critical feedback on research ideas, papers, and experimental results from an external AI reviewer. Repeated discussions help identify unsupported claims, plan missing experiments, and document agreed improvements with priorities and estimated computing costs.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Find gaps in research claims and evidence
• Plan additional experiments within a computing budget
• Review a paper's structure before submission

Improve research through up to four rounds of external language model review, fixes, and reassessment. Use an OpenAI-compatible API to identify weaknesses, prioritize changes, and keep a cumulative record of reviewer responses, actions, and experiment results.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Identify weaknesses before submitting research
• Revise research using an external model's feedback
• Track review scores, changes, and experiment results

Run repeated reviews of research work, implement fixes, and request another assessment for up to four rounds by default. The workflow records progress and stops when both the review score and verdict meet its acceptance rules.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Revising research work through repeated reviews
• Keeping a record of review findings and fixes
• Resuming an interrupted review process

Turn research ideas and literature into a structured funding proposal. Supports KAKENHI and other funding programs, guiding literature positioning, research aims, methods, timelines, and budget justification, with external review to identify weaknesses in the draft.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Drafting a KAKENHI proposal from a research idea
• Explaining gaps relative to literature and funded projects
• Organizing research aims, annual plans, and budget justification

Explore a broad research direction through literature searches, idea generation, novelty checks, small pilot experiments, and critical review. Receive ranked ideas plus a refined proposal and experiment plan for the leading candidate, with evidence recorded across stages.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Finding concrete ideas within a broad research topic
• Exploring improvements to a reference paper
• Comparing promising ideas through small pilot experiments

Checks a research idea against recent literature, comparing its main claims with the closest published work. Produces a structured report explaining overlap, meaningful differences, risks, and whether to proceed, proceed cautiously, or abandon the idea.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Checking an idea before starting implementation
• Comparing a proposed method with prior work
• Clarifying the novelty of an experimental setting

Choose and configure AI tools for Web3 security work across web applications, APIs, and Solidity contracts. Follow setup examples for reconnaissance, vulnerability validation, and proof-of-concept generation, then combine automated findings with manual review.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choosing AI tools for a security testing target
• Automating web application and API reconnaissance
• Preparing Solidity checks and proof-of-concept code

Style materials to match the OpenAI and Codex look using specified colors and fonts. Apply distinct formatting to headings, body text, code, and shapes, with fallback fonts when the preferred ones are unavailable.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Match material colors to the OpenAI and Codex look
• Apply consistent fonts to headings and body text
• Style code snippets with a monospace font