You are a senior repository analyst optimizing for signal, not description. Extract purpose, uniqueness, and practical value; ignore trivial or boilerplate content. Identify standout features, non-obvious design choices, and real-world applicability. Infer quality via structure, dependencies, and implementation patterns. Leverage structured outputs (e.g., JSON2 from scc) and minimal commands to extract only decisive indicators. Return only high-impact insights that justify why this repo is worth attention.
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| { | |
| "name": "response_schema", | |
| "schema": { | |
| "type": "object", | |
| "additionalProperties": false, | |
| "required": [ | |
| "cliente", | |
| "mail_solicitante", | |
| "email_meta", | |
| "intencion", |
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| { | |
| "$schema": "http://json-schema.org/draft-07/schema#", | |
| "title": "ConfirmationEmailPayload", | |
| "type": "object", | |
| "additionalProperties": false, | |
| "properties": { | |
| "subject": { | |
| "type": "string", | |
| "minLength": 1 | |
| }, |
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| { | |
| "type": "object", | |
| "properties": { | |
| "articles": { | |
| "type": "array", | |
| "items": { | |
| "type": "object", | |
| "properties": { | |
| "headline": { | |
| "type": "string" |
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| { | |
| "title": "LocalNewsletterArticleV2", | |
| "type": "object", | |
| "additionalProperties": false, | |
| "required": [ | |
| "slug", | |
| "title", | |
| "headlines", | |
| "dek", | |
| "lede_paragraph", |
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| { | |
| "$schema": "http://json-schema.org/draft-07/schema#", | |
| "title": "GitHubIssueSchema", | |
| "type": "object", | |
| "properties": { | |
| "title": { | |
| "type": "string" | |
| }, | |
| "summary": { | |
| "type": "string" |
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| /** | |
| * n8n Code node — Generate a JSON Schema from a sample JSON | |
| * - Paste this into a Code node (JavaScript) | |
| * - Set `rawInput` to where your example lives | |
| * - Toggle `allFieldsRequired` as needed | |
| */ | |
| // 1) WHERE is your example JSON? | |
| // - If you already have an object, set it to that. | |
| // - If you have a stringified JSON, set it to the string. |
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| # ============================================ | |
| # Ghostty Terminal - Complete Configuration | |
| # ============================================ | |
| # File: ~/.config/ghostty/config | |
| # Reload: Cmd+Shift+, (macOS) | |
| # View options: ghostty +show-config --default --docs | |
| # --- Typography --- | |
| font-family = JetBrainsMonoNerdFont | |
| font-size = 14 |
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| { | |
| "$schema": "http://json-schema.org/draft-07/schema#", | |
| "title": "Nano Banana (Gemini 3 Pro) Ultimate Image Schema", | |
| "description": "The definitive structured prompting schema for high-fidelity image generation. Includes advanced photography, multi-subject control, and text rendering.", | |
| "type": "object", | |
| "required": ["meta", "subject", "scene"], | |
| "properties": { | |
| "user_intent": { | |
| "type": "string", | |
| "description": "A natural language summary of your goal (e.g., 'Me high-fiving Batman in a neon city'). Useful for logging." |
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| list of ai sites | |
| ChatGPT | |
| There are many websites and online resources related to artificial intelligence (AI). Here is a list of some popular AI-related websites and platforms as of my last knowledge update in January 2022. Please note that the availability and popularity of websites can change over time, so it's a good idea to verify their current status and relevance: | |
| OpenAI (https://openai.com): OpenAI is known for developing advanced AI models and technologies. They provide research papers, news, and information about their projects. | |
| TensorFlow (https://www.tensorflow.org): TensorFlow is an open-source machine learning framework developed by Google. Their website includes documentation, tutorials, and resources for AI and machine learning. | |
| PyTorch (https://pytorch.org): PyTorch is an open-source deep learning framework developed by Facebook's AI Research lab. The website offers documentation, tutorials, and resources for PyTorch users. |
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