SNIPPET LIBRARY

# Quick start
1. Open https://orecot.com → Sign in
2. Upload resume (PDF or DOCX)
3. Open Zoom/Meet/Teams meeting
4. Start Orecot listening
5. AI talking points appear as questions arrive

# Example workflow: invoice chasing
# 1. Toggle Claude for Small Business in Cowork
# 2. Connect QuickBooks
# 3. Run: "Find all overdue invoices, draft chase emails, queue for my approval"
# 4. Claude returns: list of overdue invoices + drafted emails
# 5. You approve each email before send

# 3-agent team that builds a full site in parallel
claude --agent-team "manager,frontend,backend" \
  "Build a SaaS landing page with auth, billing, dashboard"

const response = await openai.chat.completions.create({
  model: "gpt-5.5",
  messages: [{ role: "user", content: prompt }],
  tools: yourToolSchemas,
});

# Example: analyze entire firmware codebase
cd ~/firmware-project
claude --effort xhigh "Review all ISR handlers in src/ for missing volatile keywords on shared variables. Check ARM Cortex-M memory barriers."

# Example: cross-compilation safety
claude "This code targets ARM Cortex-M0 with no FPU. Find any floating-point operations that need to be replaced with fixed-point math."

# Run after 5-10 sessions
/less-permission-prompts

# Review the proposed allowlist it outputs
# Accept to write to .claude/settings.json

# Launch with xhigh effort
claude --effort xhigh

# Or change mid-session
/effort xhigh

# Interactive slider (new)
/effort

# In your project directory
unzip ~/Downloads/claude-design-handoff.zip -d ./design-handoff
claude "Implement the design in ./design-handoff using our existing component library. Follow the design tokens in design-handoff/tokens.json. Generate React + Tailwind."

# Optional: prepare your codebase before upload
# Extract just the design-relevant files to keep context focused
find . -type f \( -name "*.css" -o -name "tailwind.config.*" -o -name "theme.*" -o -name "*.scss" \) \
  | head -50 | tar -czf design-system-source.tar.gz -T -

const response = await anthropic.messages.create({
  model: "claude-opus-4-7",
  max_tokens: 4096,
  messages: [{
    role: "user",
    content: [
      { type: "image", source: { type: "base64", media_type: "image/png", data: screenshotBase64 }},
      { type: "text", text: "Identify the UI components in this screenshot and output React code." }
    ]
  }]
});

# Plug Kimi into Claude Code as backend
export ANTHROPIC_BASE_URL=https://api.moonshot.cn/anthropic
export ANTHROPIC_API_KEY=your-moonshot-key
claude

import Anthropic from "@anthropic-ai/sdk";

const client = new Anthropic();

async function streamWithThinking(prompt: string) {
  const stream = await client.messages.stream({
    model: "claude-sonnet-4-6",
    max_tokens: 16000,
    thinking: {
      type: "enabled",
      budget_tokens: 10000,
    },
    messages: [{ role: "user", content: prompt }],
  });

  let thinkingText = "";
  let responseText = "";

  for await (const event of stream) {
    if (event.type === "content_block_delta") {
      if (event.delta.type === "thinking_delta") {
        thinkingText += event.delta.thinking;
        process.stdout.write("\x1b[2m"); // dim
        process.stdout.write(event.delta.thinking);
        process.stdout.write("\x1b[0m");
      } else if (event.delta.type === "text_delta") {
        responseText += event.delta.text;
        process.stdout.write(event.delta.text);
      }
    }
  }

  return { thinking: thinkingText, response: responseText };
}

streamWithThinking(
  "Design a database schema for a multi-tenant SaaS app with row-level security."
);

import google.generativeai as genai
import os

genai.configure(api_key=os.environ["GEMINI_API_KEY"])

model = genai.GenerativeModel(
    model_name="gemini-2.5-pro",
    tools=[{"google_search": {}}],
)

response = model.generate_content(
    "What are the latest updates to Claude's API in 2026?",
    generation_config=genai.GenerationConfig(
        temperature=0.1,
    ),
)

# Print grounded response
print(response.text)

# Access grounding metadata (sources)
if response.candidates[0].grounding_metadata:
    for chunk in response.candidates[0].grounding_metadata.grounding_chunks:
        print(f"Source: {chunk.web.uri}")
        print(f"Title: {chunk.web.title}")

import requests
import os

ELEVEN_API_KEY = os.environ["ELEVEN_API_KEY"]

# Step 1: Clone a voice from a short audio sample
def clone_voice(name: str, audio_path: str) -> str:
    with open(audio_path, "rb") as f:
        response = requests.post(
            "https://api.elevenlabs.io/v1/voices/add",
            headers={"xi-api-key": ELEVEN_API_KEY},
            data={"name": name},
            files={"files": (audio_path, f, "audio/mpeg")},
        )
    response.raise_for_status()
    return response.json()["voice_id"]

# Step 2: Generate speech with the cloned voice
def speak(voice_id: str, text: str, output_path: str):
    response = requests.post(
        f"https://api.elevenlabs.io/v1/text-to-speech/{voice_id}",
        headers={
            "xi-api-key": ELEVEN_API_KEY,
            "Content-Type": "application/json",
        },
        json={
            "text": text,
            "model_id": "eleven_multilingual_v2",
            "voice_settings": {"stability": 0.5, "similarity_boost": 0.8},
        },
    )
    response.raise_for_status()
    with open(output_path, "wb") as f:
        f.write(response.content)

voice_id = clone_voice("My Narrator", "sample.mp3")
speak(voice_id, "Welcome to the future of voice AI.", "output.mp3")

import Anthropic from "@anthropic-ai/sdk";

const anthropic = new Anthropic();

const response = await anthropic.messages.create({
  model: "claude-sonnet-4-6",
  max_tokens: 1024,
  messages: [{ role: "user", content: "Your prompt here" }]
});

console.log(response.content[0].text);

import Anthropic from "@anthropic-ai/sdk";

const anthropic = new Anthropic();

const stream = await anthropic.messages.stream({
  model: "claude-sonnet-4-6",
  max_tokens: 16000,
  thinking: { type: "enabled", budget_tokens: 10000 },
  messages: [{ role: "user", content: prompt }]
});

for await (const event of stream) {
  if (event.type === "content_block_delta") {
    if (event.delta.type === "thinking_delta") {
      process.stdout.write(event.delta.thinking);
    }
    if (event.delta.type === "text_delta") {
      process.stdout.write(event.delta.text);
    }
  }
}

# Install
npm install -g @anthropic-ai/claude-code

# Navigate to your project and start
cd your-project
claude

# Give it a task
# > Add rate limiting to the /api/auth/login endpoint using Redis

import google.generativeai as genai

genai.configure(api_key=os.environ["GEMINI_API_KEY"])
model = genai.GenerativeModel("gemini-2.5-pro")

# Pass entire codebase — 1M tokens available
with open("entire_codebase.txt") as f:
    code = f.read()

response = model.generate_content(f"Summarize this codebase:\n{code}")
print(response.text)

import google.generativeai as genai

genai.configure(api_key=os.environ["GEMINI_API_KEY"])
model = genai.GenerativeModel("gemini-2.5-pro")

response = model.generate_content(
    "What happened in AI this week?",
    tools=[{"google_search_retrieval": {}}]
)
print(response.text)

# Access source citations
for chunk in response.candidates[0].grounding_metadata.grounding_chunks:
    print(f"Source: {chunk.web.uri}")

import requests
import os

ELEVEN_API_KEY = os.environ["ELEVEN_API_KEY"]

url = "https://api.elevenlabs.io/v1/voices/add"
headers = {"xi-api-key": ELEVEN_API_KEY}
files = {"files": open("sample.mp3", "rb")}
data = {"name": "MyVoice", "description": "Custom voice"}

response = requests.post(url, headers=headers, files=files, data=data)
voice_id = response.json()["voice_id"]
print(f"Voice cloned: {voice_id}")

import { generateText } from "ai";
import { anthropic } from "@ai-sdk/anthropic";

const { text } = await generateText({
  model: anthropic("claude-sonnet-4-6"),
  prompt: "Explain RAG in one paragraph"
});

console.log(text);

// Swap provider in one line — same API
// import { openai } from "@ai-sdk/openai";
// model: openai("gpt-4o")

const ws = new WebSocket(
  "wss://api.openai.com/v1/realtime?model=gpt-4o-realtime-preview",
  {
    headers: {
      "Authorization": `Bearer ${process.env.OPENAI_API_KEY}`,
      "OpenAI-Beta": "realtime=v1"
    }
  }
);

ws.on("open", () => {
  ws.send(JSON.stringify({
    type: "session.update",
    session: {
      modalities: ["text", "audio"],
      voice: "alloy"
    }
  }));
});

ws.on("message", (data) => {
  const event = JSON.parse(data.toString());
  if (event.type === "response.audio.delta") {
    // Handle audio chunk
  }
  if (event.type === "response.text.delta") {
    process.stdout.write(event.delta);
  }
});