How do I install the Codex Reset Radar skill?

Run npx skillmds@latest add lord1egypt/codex-reset-radar in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Codex Reset Radar safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: makes network calls, reads secrets. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Codex Reset Radar?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Codex Reset Radar free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Codex Reset Radar?

Lord1Egypt (@lord1egypt) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Codex Reset Radar by lord1egypt — Agent Skill

Name: Codex Reset Radar
Rating: 4.666666666666667 (3 reviews)
Author: Lord1Egypt

Codex Reset Radar

Monitor Codex usage reset windows via codex-reset-radar.pages.dev. Polls current.json, detects window open/close, prediction level changes, and probability jumps. Pushes alerts via OpenClaw cron only when state changes, using the default agent chat channel. LLM only processes script-generated JSON diffs — minimal token burn.

Lord1Egypt Updated Sep 8, 2026 2 repo stars

File contents

Codex Reset Radar — Usage Reset Window Monitor

Monitors the Codex Reset Radar current.json endpoint to detect Codex usage quota reset windows ("speed windows"), pushing alerts via OpenClaw cron to the default agent chat channel.

How It Works

Cron triggers
     │
     ▼
① Data collection: python3 scripts/codex-radar-check.py
   → fetch current.json + compare against local cache
     │
     ▼
② JSON diff: outputs has_changes + events[] or has_changes: false
   → no changes → agent replies NO_REPLY (silent)
     │
     ▼
③ LLM formatting: reads JSON diff only
   → formats into a friendly chat message
     │
     ▼
④ Chat push: announce → user session (default chat channel)

Detection Script

scripts/codex-radar-check.py — stdlib only, zero dependencies:

Fetches https://codex-reset-radar.pages.dev/current.json
Compares against cache/codex-radar-last.json from previous run
Creates baseline on first run

Change types detected:

Event	Trigger	Output type
Window opened	`window_open` false→true	`window_opened`
Window closed	`window_open` true→false	`window_closed`
Status change	`status` field changed	`status_change`
New window	`last_window.id` changed	`new_window`
Prediction change	`prediction.level` changed	`prediction_change`
Probability jump	`prediction.probability_24h` crosses 0.1 threshold	`prediction_probability_change`

Output JSON Examples

No changes:

{"has_changes": false}

Changes detected:

{
  "has_changes": true,
  "events": [
    {"type": "window_opened", "detail": "Codex usage reset window opened", "opened_at": "2026-05-24T08:21:33+08:00", "scope": "Codex users"}
  ],
  "current_status": {
    "window_open": true,
    "status": "open",
    "last_window_id": "codex-speed-window-2026-05-24-codex",
    "prediction_level": "low",
    "probability_24h": 0.06
  }
}

Installation

clawhub install codex-reset-radar

Cron Setup

Create an OpenClaw cron job (recommended: hourly 8 AM–11 PM, silent overnight). The delivery target will automatically use your default agent chat channel:

{
  "name": "Codex Reset Radar Monitor",
  "schedule": {"kind": "cron", "expr": "0 8-23 * * *", "tz": "Asia/Shanghai"},
  "sessionTarget": "isolated",
  "payload": {
    "kind": "agentTurn",
    "timeoutSeconds": 60,
    "lightContext": true,
    "message": "Codex Reset Radar monitor.\n1. cd ~/.openclaw/workspace && python3 skills/codex-reset-radar/scripts/codex-radar-check.py\n2. If has_changes: false, reply NO_REPLY\n3. If changes detected, format and push to default chat channel"
  }
}

💡 The cron job will push alerts to whatever chat channel your OpenClaw agent uses by default (Feishu, Discord, Telegram, etc.). No channel-specific config needed.

Recommended schedules:

0 8-23 * * * — hourly during waking hours, silent 0-7
*/10 * * * * — every 10 minutes (urgent monitoring)

Design Principles

LLM only sees JSON diffs — no raw RSS/HTML semantic analysis, minimal token usage
Zero-cost silence — has_changes: false → agent replies NO_REPLY → nothing pushed to chat
Stdlib only — uses json, urllib, datetime, os; zero external dependencies
Fault-tolerant — network errors output {"has_changes": false, "error": "..."}, never false-trigger or crash
Channel-agnostic — works with any chat channel (Feishu, Discord, Telegram, etc.) via OpenClaw's delivery system

---name: codex-reset-radardescription: Monitor Codex usage reset windows via codex-reset-radar.pages.dev. Polls current.json, detects window open/close, prediction level changes, and probability jumps. Pushes alerts via OpenClaw cron only when state changes, using the default agent chat channel. LLM only processes script-generated JSON diffs — minimal token burn.---# Codex Reset Radar — Usage Reset Window MonitorMonitors the [Codex Reset Radar](https://codex-reset-radar.pages.dev/) `current.json` endpoint to detect Codex usage quota reset windows ("speed windows"), pushing alerts via OpenClaw cron to the default agent chat channel.## How It Works```Cron triggers │ ▼① Data collection: python3 scripts/codex-radar-check.py → fetch current.json + compare against local cache │ ▼② JSON diff: outputs has_changes + events[] or has_changes: false → no changes → agent replies NO_REPLY (silent) │ ▼③ LLM formatting: reads JSON diff only → formats into a friendly chat message │ ▼④ Chat push: announce → user session (default chat channel)```### Detection Script`scripts/codex-radar-check.py` — stdlib only, zero dependencies:- Fetches `https://codex-reset-radar.pages.dev/current.json`- Compares against `cache/codex-radar-last.json` from previous run- Creates baseline on first run**Change types detected:**| Event | Trigger | Output type ||-------|---------|-------------|| Window opened | `window_open` false→true | `window_opened` || Window closed | `window_open` true→false | `window_closed` || Status change | `status` field changed | `status_change` || New window | `last_window.id` changed | `new_window` || Prediction change | `prediction.level` changed | `prediction_change` || Probability jump | `prediction.probability_24h` crosses 0.1 threshold | `prediction_probability_change` |### Output JSON ExamplesNo changes:```json{"has_changes": false}```Changes detected:```json{ "has_changes": true, "events": [ {"type": "window_opened", "detail": "Codex usage reset window opened", "opened_at": "2026-05-24T08:21:33+08:00", "scope": "Codex users"} ], "current_status": { "window_open": true, "status": "open", "last_window_id": "codex-speed-window-2026-05-24-codex", "prediction_level": "low", "probability_24h": 0.06 }}```## Installation```bashclawhub install codex-reset-radar```## Cron SetupCreate an OpenClaw cron job (recommended: hourly 8 AM–11 PM, silent overnight).The delivery target will automatically use your default agent chat channel:```json{ "name": "Codex Reset Radar Monitor", "schedule": {"kind": "cron", "expr": "0 8-23 * * *", "tz": "Asia/Shanghai"}, "sessionTarget": "isolated", "payload": { "kind": "agentTurn", "timeoutSeconds": 60, "lightContext": true, "message": "Codex Reset Radar monitor.\n1. cd ~/.openclaw/workspace && python3 skills/codex-reset-radar/scripts/codex-radar-check.py\n2. If has_changes: false, reply NO_REPLY\n3. If changes detected, format and push to default chat channel" }}```> 💡 The cron job will push alerts to whatever chat channel your OpenClaw agent uses by default (Feishu, Discord, Telegram, etc.). No channel-specific config needed.**Recommended schedules:**- `0 8-23 * * *` — hourly during waking hours, silent 0-7- `*/10 * * * *` — every 10 minutes (urgent monitoring)## Design Principles- **LLM only sees JSON diffs** — no raw RSS/HTML semantic analysis, minimal token usage- **Zero-cost silence** — `has_changes: false` → agent replies `NO_REPLY` → nothing pushed to chat- **Stdlib only** — uses `json`, `urllib`, `datetime`, `os`; zero external dependencies- **Fault-tolerant** — network errors output `{"has_changes": false, "error": "..."}`, never false-trigger or crash- **Channel-agnostic** — works with any chat channel (Feishu, Discord, Telegram, etc.) via OpenClaw's delivery system

Frequently asked questions