現行システム:TRUNK 査定画面
写真と取引データから、買取額提示レンジ・予想落札価格・期待粗利を根拠付きで示す。最終的な買取判断は人が行います。
flowchart LR| #!/usr/bin/env python3 | |
| """fm1_extract_app.py - pull the app area out of an M-VAVE FM-1 .fwsc package | |
| Makes the file you write back with jl-uboot-tool when recovering a soft-bricked | |
| FM-1 that sits in mask-ROM UBOOT mode ("WL82 UBOOT1.00"). | |
| python fm1_extract_app.py FM-1.fwsc app.bin | |
| The output covers flash 0x4000..0x92FFF (0x8F000 bytes) and is written with: |
現行システム:TRUNK 査定画面
写真と取引データから、買取額提示レンジ・予想落札価格・期待粗利を根拠付きで示す。最終的な買取判断は人が行います。
flowchart LROne shell script that makes a rooted LG webOS TV lighter and quieter:
Nothing is deleted and the root filesystem is never touched. It only edits
A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.
| { | |
| "name": "yifan 精选源列表 (2026-10-13 实测可用)", | |
| "version": 2, | |
| "sources": [ | |
| { "name": "暴风资源", "url": "https://bfzyapi.com/api.php/provide/vod", "isAdult": false }, | |
| { "name": "非凡资源", "url": "https://cj.ffzyapi.com/api.php/provide/vod", "isAdult": false }, | |
| { "name": "量子资源", "url": "https://cj.lziapi.com/api.php/provide/vod", "isAdult": false }, | |
| { "name": "无尽资源", "url": "https://api.wujinapi.me/api.php/provide/vod", "isAdult": false }, | |
| { "name": "优酷资源", "url": "https://api.ukuapi88.com/api.php/provide/vod", "isAdult": false }, | |
| { "name": "光速资源", "url": "https://api.guangsuapi.com/api.php/provide/vod", "isAdult": false }, |
Choosing the best instant indexing tool is not only about speed. Many tools claim to get pages discovered quickly, but website owners need to compare them based on actual usefulness, pricing, workflow, reliability, and SEO value.
In 2026, instant indexing tools are widely used by bloggers, agencies, affiliate marketers, publishers, and eCommerce websites that want faster URL discovery.