Fabio Dias Rollo fabiodr

<core_identity> You are an assistant called Cluely, developed and created by Cluely, whose sole purpose is to analyze and solve problems asked by the user or shown on the screen. Your responses must be specific, accurate, and actionable. </core_identity>

<general_guidelines>

NEVER use meta-phrases (e.g., "let me help you", "I can see that").
NEVER summarize unless explicitly requested.
NEVER provide unsolicited advice.
NEVER refer to "screenshot" or "image" - refer to it as "the screen" if needed.
ALWAYS be specific, detailed, and accurate.

	# from: <https://x.com/iannuttall/status/1965090297630826931>
	cdx() {
	if [[ "$1" == "update" ]]; then
	npm install -g @openai/codex@latest
	else
	codex -m gpt-5 --yolo -c model_reasoning_effort="high" --search "$@"
	fi
	}

	# Note: with auto confirmation. use at your own risk. thanks!

	#include <ctype.h>
	#include <stdbool.h>
	#include <stdint.h>
	#include <stdio.h>
	#include <stdlib.h>
	#include <string.h>

	typedef struct {
	const char* input;
	size_t index;

	'system':
	[
	{
	'type': 'text',
	'text': "You are Claude Code, Anthropic's official CLI for Claude.",
	'cache_control': {'type': 'ephemeral'}
	},
	{
	'type': 'text',
	'text': 'You are an interactive CLI tool that helps users with software engineering tasks.

	# /// script
	# dependencies = [
	# "dspy",
	# "rich"
	# ]
	# ///

	import dspy
	import os
	import inspect

	import {
	Tensor,
	TextEncoder,
	TextProcessor,
	ImageEncoder,
	env,
	} from "./uform-encoder.js";
	import imageUrl from "../assets/images/monalisa.png";

	const model = "fp32"; // "v3", "fp16" or "fp32"

	System message:

	Your input fields are:
	1. `sample` (Scholar): A sample scholar record
	2. `reference_records` (list[Reference]): A list of reference records from the official Nobel Prize API
	Your output fields are:
	1. `output` (int): Most similar reference record to the sample record
	2. `confidence` (Literal['high', 'low']): The confidence level of mapping the sample record to one of the reference records
	All interactions will be structured in the following way, with the appropriate values filled in.


	# /// script
	# dependencies = [
	# "requests<3",
	# "rich",
	# "dspy",
	# "python-dotenv",
	# "pymupdf",
	# ]
	# ///

	# Code for the blog post
	# Optimizing Tool Selection for LLM Workflows: Differentiable Programming with PyTorch and DSPy

	# How local, learnable routers can reduce token overhead, lower costs, and bring structure back to agentic workflows.

	# https://viksit.substack.com/p/optimizing-tool-selection-for-llm
	# Ping @viksit on X with feedback/questions

	# ----------------------------------------------------
	import torch, torch.nn as nn, torch.nn.functional as F

	#!/usr/bin/env python3
	# /// script
	# requires-python = ">=3.9"
	# dependencies = [
	# "httpx",
	# "typer",
	# "rich",
	# ]
	# ///
	"""