القائمة
Summarize a list of numbers — count, mean, and standard deviation. Use when the user gives you numbers and wants quick descriptive statistics.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens). SKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST
Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks.
Knowledge and utilities for creating animated GIFs and chat emoji from code with Pillow. Provides size presets, validation tools, and animation concepts. Use when the user wants an animated GIF or emoji, e.g. "make me a GIF of X doing Y" or "an animated emoji of Z."
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this skill.
| name | hello-data |
| description | Summarize a list of numbers — count, mean, and standard deviation. Use when the user gives you numbers and wants quick descriptive statistics. |
| license | MIT |
| compatibility | Requires python3 |
| metadata | {"author":"ada-example","version":"1.0"} |
A tiny example skill showing how Ada runs a skill's bundled Python script inside the AIO sandbox.
The user gives you a set of numbers and wants a quick summary — count, mean, and standard deviation.
Call the summarize script, passing each number as a separate string argument. For the numbers
4, 8, 15, 16, 23, 42 call it with ["4", "8", "15", "16", "23", "42"]. The script prints a JSON
object with count, mean, and stdev; read that back to the user in one short sentence.
statistics), so it needs no extra packages.