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Found 546 Skills
AI Image Generation Skill, using the latest ChatGPT image generation model gpt-image-2-all. This skill is applied when users need to generate images, visual infographics, create graphics, or edit/modify/adjust existing images. Based on the image generation service of the latest ChatGPT image generation model gpt-image-2-all from APIYI Platform (https://api.apiyi.com/), no external network access is required. The model is charged per image at $0.03 per piece, supporting text-to-image generation, single image editing, multi-image fusion, and natural language-based image modification, with high text restoration accuracy and friendly Chinese prompts. The size is controlled by prompt description (no explicit size parameter). Key differences from NanoBanana2: no size parameter, need to describe the size at the beginning of the prompt; unified $0.03 per image with no resolution tiering; the conversational endpoint /v1/chat/completions is the recommended one.
Format a final summary message for Linear. Your output is automatically streamed to the Linear agent session — just format it well, do not post it yourself.
Manages CockroachDB cluster capacity across all tiers. Self-Hosted covers node decommissioning for permanent removal and adding nodes for expansion. Advanced/BYOC covers scaling node count and machine size via Cloud Console, API, or Terraform. Standard covers adjusting provisioned compute (vCPUs). Basic auto-scales — guidance covers spending limits and cost management. Use when scaling capacity up or down, permanently removing nodes, or managing costs.
Match spoken edit beats to candidate B-roll assets using a normalized transcript, subtitle chunking, optional A-roll analysis, and a reusable B-roll catalog. Use this when the goal is to decide what B-roll should support each beat, not just to list assets or describe the video.
Bootstrap a nao agent for a project — gather warehouse + scope + extra-context info in one round, look up the warehouse-specific config from nao docs, write nao_config.yaml, run nao init + nao sync, set up the LLM key, and generate the first RULES.md. Use when the user has just decided to use nao on a new project. Only for first-time setup; for editing rules, generating tests, or reviewing an existing context, use write-context-rules / create-context-tests / audit-context.
Adapts experiences across cultures and languages — not just translation, but cultural reconception. Part of the Intent design strategy system. When a product enters a new market, everything is in play: information density, navigation patterns, color meaning, icon comprehension, date formats, trust signals, payment flows, and the fundamental assumptions about how people make decisions. Trigger when: planning international expansion, auditing i18n readiness, adapting designs for RTL languages, reviewing cultural assumptions in a design, preparing localization test plans, or when someone says "we need to launch in [country]" and the plan is "just translate it." Also trigger for compliance reviews across markets (GDPR, PIPL, accessibility laws).
This skill is applicable when users explicitly request to 'write/generate NSFC budget specification', 'write budget explanation', 'generate budget.tex / budget.pdf', or 'write NSFC budget justification'. Based on the user's proposal text or supplementary materials, output a submittable budget specification LaTeX project and render `budget.pdf`. If the user does not specify a working directory, you must pause and ask them to specify it first. ⚠️ Not applicable: Users only want to understand budget principles; users only want budget table figures without writing the specification; or users are in the 2026 Youth A/B/C default lump-sum scenario where no budget specification is required.
The local-first Craigslist watcher and triage tool that knows what's a repost, what's a scam, and what just dropped in price. Trigger phrases: `watch craigslist for`, `find new listings on craigslist`, `craigslist deal alert`, `scan craigslist across cities`, `craigslist repost`, `craigslist scam check`, `use craigslist-pp-cli`, `run craigslist-pp`.
Analyze a Materialize environment for health, performance, and optimization opportunities using the MCP Developer endpoint. Use this skill when someone wants to check environment health, investigate performance issues, troubleshoot stale materialized views, diagnose memory pressure, audit resource utilization, or get optimization recommendations. Trigger this even if the user just says "check my environment", "why is my MV stale", "why is my cluster slow", or "what can I optimize".
End-to-end epidemiological data analysis — from research question to statistical report. Covers study design assessment, dataset discovery and download, data wrangling, confounder adjustment, regression modeling, sensitivity analysis, visualization, and biological interpretation. Integrates ToolUniverse tools for dataset discovery, literature search, and biological context with Python code execution for data analysis. Use whenever users ask to analyze health data, study disease risk factors, assess exposure-outcome relationships, or conduct observational epidemiology. Also use when users want to run regression on clinical/survey data, calculate odds ratios or hazard ratios from a dataset, adjust for confounders, or produce a Table 1. If the task involves downloading a health dataset and running statistical analysis on it, this is the right skill.
Cultural adaptation for translated content. Run AFTER blog-translate completes. Adjusts brand examples, CTAs, legal references, and formality for the target market (German, French, Japanese, Spanish, etc.). Deep cultural adaptation of translated blog posts. Goes beyond translation to swap brand examples, adapt CTAs, substitute legal references, localize statistic sources where possible, and adjust formality (Sie/du, tu/vous, formal/informal). Built-in profiles for DACH, Francophone, Hispanic, and Japanese markets, plus a custom-locale template. Makes content feel locally authored, not translated. Use when user says "localize blog", "blog localize", "cultural adaptation", "adapt for Germany", "adapt for France", "lokalisieren", "localiser", "adaptar".
Risk-return optimisation for investment portfolios via Longbridge — builds risk-adjusted return-optimal portfolios based on fund size, risk preference (conservative / balanced / aggressive), and investment horizon. Asset allocation across equities / bonds / cash / commodities / alternatives. Evaluates current portfolio efficiency versus the efficient frontier. Triggers: "风险收益优化", "组合效率", "有效前沿", "风险偏好配置", "最优组合", "风险调整收益", "大类资产配置", "投资组合优化", "風險收益優化", "組合效率", "有效前沿", "風險偏好配置", "最優組合", "risk-return optimization", "portfolio efficiency", "efficient frontier", "risk preference", "optimal portfolio", "risk-adjusted return", "asset class allocation", "portfolio optimisation", "mean variance".