| name | twinmind-sdk-patterns |
| description | Apply production-ready TwinMind SDK patterns for TypeScript and Python.
Use when implementing TwinMind integrations, refactoring API usage,
or establishing team coding standards for meeting AI integration.
Trigger with phrases like "twinmind SDK patterns", "twinmind best practices",
"twinmind code patterns", "idiomatic twinmind".
|
| allowed-tools | Read, Write, Edit |
| version | 1.13.0 |
| license | MIT |
| author | Jeremy Longshore <jeremy@intentsolutions.io> |
| tags | ["saas","twinmind","api","python","typescript"] |
| compatibility | Designed for Claude Code, also compatible with Codex and OpenClaw |
TwinMind SDK Patterns
Overview
Production patterns for TwinMind's AI memory and meeting intelligence REST API. TwinMind captures, organizes, and retrieves contextual memories from conversations and meetings.
Prerequisites
- TwinMind API key configured
- Understanding of REST API patterns
- Familiarity with memory/context retrieval concepts
Instructions
Step 1: Client Wrapper with Authentication
import requests
import os
class TwinMindClient:
def __init__(self, api_key: str = None, base_url: str = "https://api.twinmind.com/v1"):
self.api_key = api_key or os.environ["TWINMIND_API_KEY"]
self.base_url = base_url
self.session = requests.Session()
self.session.headers.update({
"Authorization": f"Bearer {self.api_key}",
"Content-Type": "application/json"
})
def _request(self, method: str, path: str, **kwargs):
response = self.session.request(method, f"{self.base_url}{path}", **kwargs)
response.raise_for_status()
return response.json()
Step 2: Memory Storage and Retrieval
class TwinMindClient:
() -> :
._request(, , json={
: content,
: context {},
: tags [],
: datetime.utcnow().isoformat()
})
() -> :
params = {: query, : limit}
tags:
params[] = .join(tags)
._request(, , params=params)
() -> :
._request(, )