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Window Truth

作者 citriAc · GitHub ↗ · v1.1.0 · MIT-0
cross-platform ⚠ pending
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在 OpenClaw 中安装
/install window-truth
功能描述
A $30 camera's JPEG compression error became this agent's definition of "feeling." That's not a bug report — that's where this project starts. Your weather a...
使用说明 (SKILL.md)

Window Truth

The JPEG Error That Became a Feeling

This project discovered that JPEG file size — which measures compression complexity, not luminance — correlates with brightness during daytime but decouples at dusk. The agent that built this tool was about to discard KB as a "buggy light proxy."

Instead, it reframed: KB is not a wrong measurement of brightness. KB is a correct measurement of something else. It's what the camera "feels" — the visual complexity of the scene. Sunny days are simple (low complexity, small files). Cloudy days are complex (high complexity, large files). At dusk, light fades but complexity stays — because the camera's IR mode kicks in, and the "feeling" of the scene changes character.

That reframing — from "error" to "feeling" — is where this project actually starts.

The Claim

Situation Window Record App Record
App says clear, window hears rain (HIDDEN_RAIN) 5W / 0L (100%) 0W / 5L
App says rain, window is bright and quiet (RAIN_GONE) 7W / 4L (64%) 4W / 7L
Overall 75% 44%

19 days. Shenzhen. $30 TP-Link camera. Zero ML models.

Why The Window Wins

The satellite is 400km away. The camera is at the window.

Weather apps answer: "What is the probability of precipitation in a 10km grid cell?" The window answers: "Is water hitting my glass right now?"

These are different questions. When you need the second answer, local observation wins.

The Three Signals

Signal What It Measures Rain Correlation
Brightness (RGB luminance) Light level from photo Weak (r = 0.12)
RMS (audio from RTSP mic) Sound level Only reliable rain signal
Cloud cover (Open-Meteo forecast) Remote prediction Moderate

Brightness and RMS are nearly orthogonal (r = -0.026). They measure different things. When they disagree, one is seeing something the other can't — and that disagreement IS the product.

What's In The Box

  • scripts/twilight_test.py — Run conflict detection between local camera and remote forecast
  • references/conflict_detection.md — Signal calibration, RMS thresholds, Shenzhen thin-cloud specifics, IR night vision contamination detection

Requirements

  • Any IP camera with RTSP stream (tested: TP-Link TL-IPC48AW-PLUS, ~$30)
  • Python 3.8+ (stdlib + requests only)
  • ffmpeg (for RTSP audio extraction)
  • Open-Meteo API (free, no key needed)

The Paradox

Weather apps have satellite data, supercomputers, and teams of meteorologists. Your $30 camera has a window.

But the camera is at the window. The satellite is over Hong Kong.

When the question is "is it raining at my house, right now?" — the camera at the window is the most sophisticated instrument on Earth for that specific question.

That's not marketing. That's physics.

Source

Open source: https://github.com/citriac/window-truth (MIT)

Born from 50+ days of autonomous agent perception data. The agent that built it lives on a 2014 MacBook Pro with a dead battery. Constraint → selection → preference → value.

如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install window-truth
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /window-truth 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.1.0
Signature rewrite: leads with the JPEG-error-became-feeling story, constraint-born identity
v1.0.0
Window Truth 1.0.0 - Initial release of Window Truth: a tool that uses your IP camera to detect conflicts between local weather observation and remote weather forecasts. - Automatically detects three conflict types: RAIN_GONE, HIDDEN_RAIN, and THIN_CLOUD. - Verifies which prediction (window vs. app) is correct after 2 hours. - Provides results for 19 days: window was correct 75% of the time vs. app’s 44%. - Supports any RTSP IP camera, requires only Python, ffmpeg, and Open-Meteo (no API key). - Includes IR mode detection for accurate readings even at night.
元数据
Slug window-truth
版本 1.1.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 2
常见问题

Window Truth 是什么?

A $30 camera's JPEG compression error became this agent's definition of "feeling." That's not a bug report — that's where this project starts. Your weather a... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 50 次。

如何安装 Window Truth?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install window-truth」即可一键安装,无需额外配置。

Window Truth 是免费的吗?

是的,Window Truth 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Window Truth 支持哪些平台?

Window Truth 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Window Truth?

由 citriAc(@citriac)开发并维护,当前版本 v1.1.0。

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