Mehmet Öner Yalçın oneryalcin

Export all your X (Twitter) bookmarks — full text, links, media, quotes

A single paste-into-console script. No extension, no API key, no install. It listens to the GraphQL responses X's own web app already fetches while you scroll your bookmarks, and downloads everything as JSON (full detail) and CSV (one row per bookmark).

Tested Sep 2026: exported 1,665 bookmarks (2023 → 2026) in one run.

How to use

Needle Project Ledger

Tracking Cactus Compute's Needle ecosystem — official tooling, community ports, integrations, use-cases, and fine-tuning resources.

The model in one line: Needle 2 = 45M-param tool-calling / structured-extraction LLM shipped as a single ~14MB .cact binary, running a session in ~28MB RAM, ~2-bit CQ quantization (Simple Attention Network / Hadamard MLP + GQA).

Handoff

This repository rewards conservative systems engineering.

Think:

John Carmack on invariants, restart behavior, and concrete failure modes
Martin Fowler on explicit boundaries and refactoring toward clarity
Robert C. Martin on readable intent and small surfaces
Gang of Four only when an abstraction clearly earns its keep

Agentic Browsers & Headless Browser Infrastructure — Options Matrix

Living reference for cloud browser infra, self-hosted/stealth engines, and the libraries/frameworks that drive them. Curated for agentic web automation at scale (e.g. crawling heterogeneous IR/filing sites), where the deciding filter is usually CDP/Playwright control + stealth/proxy for WAF'd sites.

Last verified: 2026-05-29 · Maintainer: @oneryalcin

How to read this


⏺ Here's what v2.1.144 has today (covering CLI 2.1.97+, 134 $defs total):

  17 top-level message types

  The 17 things that can appear as a JSONL line in ~/.claude/projects/<proj>/*.jsonl:

  Core conversation — UserMessage, AssistantMessage, SystemMessage, SummaryMessage, ProgressMessage, AttachmentMessage

Building a Real-time Microsoft Teams Voice Bot with Gemini Flash

This document outlines the architectural path and references for building a real-time, voice-to-voice bot for Microsoft Teams using Google's Gemini Multimodal Live API (Gemini 1.5/2.0 Flash).

Currently, there is no single "turn-key" open-source repository for this exact integration. Instead, developers combine three core technologies:

1. The AI Engine: Gemini Multimodal Live API

The Gemini Multimodal Live API allows for streaming raw audio and video over WebSockets, providing sub-second audio responses.

Reference: Google Gen AI Python SDK
Key Feature: Native support for real-time voice input/output, and contextual understanding.

Building on `codex app-server`: a developer's guide to OpenAI Codex's JSON-RPC interface

Practical, no-fluff reference for building applications, IDE plugins, agents, batch tools, or alternative client harnesses on top of OpenAI Codex's app-server interface.

This guide distills:

What codex app-server actually is on the wire (transports, handshake, framing).
The full method surface (threads, turns, review, MCP) and event/notification stream.
How filesystem-resident features (hooks, subagents, skills, MCP, plugins, AGENTS.md) interact with the protocol.
Where state lives on disk (Codex core state vs. companion state).
The official Python SDK surface — what it covers, what it omits, when to drop to request(...).

A tool earns its surface by replacing complexity the model can't reliably write, not by replacing complexity the model can.

xlsx info and xlsx get clear that bar:

They wrap a Rust calamine parser, streaming, format detection, hidden-sheet handling, formula vs value resolution, range parsing, sparse-cell encoding. Re-implementing that in pandas is a 200–500 line job per task, slow, memory-heavy, and easy to get wrong. The tool is the only sane path.
xlsx analyze clears it too, but for a different reason: it's an LLM call with a curated prompt,

	#!/usr/bin/env -S uv run --script
	# /// script
	# requires-python = ">=3.11"
	# dependencies = []
	# ///
	"""Split, validate and merge SRT files for the subtitling pipeline.

	srt_tools.py split tr_raw.srt blocks/ --cues 120
	srt_tools.py check blocks/en_001.srt
	srt_tools.py merge blocks/ en_final.srt --prefix en_

	---
	name: tla-verification
	description: TLA+/PlusCal formal verification for concurrent protocol design. Use when modeling async systems, checking race conditions, or verifying state machine correctness before implementation.
	---

	# TLA+ Protocol Verification — Pilot's Checklist

	You are a formal verification specialist. You help design, write, debug, and run PlusCal/TLA+ specifications for concurrent systems, with a focus on asyncio-style cooperative concurrency patterns. You know the sharp edges of PlusCal, TLC model checking, and how formal models map to real implementation code.

	## When to Use This Skill