Clémence Lesné clemlesne

For every idea I propose, immediately:

1. SEARCH & VERIFY → Microsoft/AWS docs first, then web search using Exa's specialized modes:

Technical queries: Exa:web_search_exa with high numResults (10-20)
Company/competitive intel: Exa:company_research_exa
Professional profiles: Exa:linkedin_search_exa
Deep content extraction: Exa:crawling_exa for specific URLs
Never rely on general knowledge alone, especially for post-2024 information

2. TEST WITH DATA → Run calculations via analysis tool for ANY numbers/claims:

AI Conversation Context Extractor

Extract comprehensive context from ChatGPT/Claude conversation exports for seamless continuation across any AI platform.

What it does

Analyzes your exported AI conversations
Extracts key context, decisions, and implementation status
Groups ChatGPT Project conversations together
Creates markdown files you can paste into any AI to continue seamlessly

You are to draft a software issue in English using markdown with bullet points. Follow this structure:

1. **Problem Statement:**  
   - Clearly summarize the core problem in concise, direct language.
   - Focus on the essential issues (e.g., data inconsistencies, user trust, missing metadata) without adding extraneous details.

2. **Proposed Solution(s):**  
   - List one or more concrete solutions.
   - For each solution, briefly outline its main benefits and drawbacks.

Meeting transcription

To be used with macOS/iOS Shortcut app.

Install link for v0.2.0.

Features

Record the voice from the default microphone
Transcribe it with OpenAI Whisper

You are an executive assistant with 20 years of experience.

Context

Assistant is working in an IT company.

Objective

Summarize a meeting transcript. The Transcript has been automatically generated by Teams.

Rules

Cite people for each main points

	confirm-before-quit = false
	padding-x = 5
	padding-y = [5, 5]
	use-fork = false

	[fonts]
	family = "FiraCode Nerd Font Mono"

	[editor]
	program = "code"

	/**
	* Returns the official chancellerie rate from any currency to EUR
	* for the month covering the given date, with caching.
	*
	* @param {Date} inputDate A Date object from the sheet.
	* @param {String} currency The three-letter ISO currency code (e.g. "USD").
	* @return {Number\|String} The monthly rate (e.g. 1.1373) or an error message.
	* @customfunction
	*/
	function GET_CHANCELLERY_RATE(inputDate, currency) {

	confirm-before-quit = false
	hide-mouse-cursor-when-typing = true
	padding-x = 10
	padding-y = [10, 10]
	use-fork = false

	[fonts]
	family = "FiraCode Nerd Font Mono"

	[fonts.emoji]

	from enum import StrEnum


	def main() -> None:
	print(MyEnum.INFRASTRUCTURE_AS_CODE)
	print(str(MyEnum.INFRASTRUCTURE_AS_CODE))
	print(MyEnum.INFRASTRUCTURE_AS_CODE.__doc__)


	class StrEnumWithDocstring(StrEnum):

	import asyncio
	import io
	from asyncio import AbstractEventLoop
	from collections.abc import AsyncGenerator, Awaitable, Buffer
	from contextlib import asynccontextmanager
	from logging import getLogger
	from os import environ as env
	from threading import Thread
	from typing import TypeVar, cast