Research

13.77-Day Dip: Codex Spotted a Possible Planet Hiding in 17-Year-Old Kepler Data

  • Level Advanced
  • Setup1–3 hrs (estimated)
  • Evidence Some evidence
  • CostNot stated in source
  • No-codeNo
CodexSource-linked

What they did

A hobbyist used Codex to build tools that scan public NASA Kepler and TESS data for stars that dim on a schedule. It flagged an uncatalogued dip every 13.77 days around KIC 5689121, a small red star about 970 light-years away. It sits 7.1 arcseconds from a much brighter star, which is probably why it was missed. If it's real, it's a planet about 2.5 to 3 times Earth's size, and he published all the evidence online.

How it went

A shortlist of repeating dips in public telescope data, each with plots and an honest false-alarm check.

Worth knowing

  • Still only a candidate: his own validation score is about 6.9%, and it needs telescope follow-up (infrared or adaptive-optics imaging, such as Keck) before anyone can call it a planet. The post title says ChatGPT; the post itself says the work was done with Codex.

Prompt

Cleaned version rewritten from the source — not a direct quote.

Help me search public [Kepler / TESS] light curves for possible transiting planets. Download the data for [star or field] with [lightkurve], clean up the trends, run a box least squares search, and flag repeating dips that aren't in the known planet catalogues. For each signal, try hard to prove it is NOT a planet: check nearby bright stars, odd versus even dip depths, and data you held back from the search. Show me the plots and say plainly how likely it is to be a false alarm.

Recommended

Try it in Grok Bot

  1. Copy the prompt (button below).
  2. Open Grok Bot chat and paste it. Replace any [bracketed] placeholders.
  3. Connect the listed tools (as needed) as connectors when Grok Bot asks.
  4. If the task repeats, ask: "Make this a daily routine."

Alternatives: the same prompt works in Codex, Claude, ChatGPT Agent, OpenClaw.

Set it up

Stack: Codex + public Kepler/TESS data

  1. Read the original source for full context.
  2. Connect the tools your agent needs.
  3. Paste the prompt and replace [bracketed] placeholders.
  4. Run once manually and check the output before scheduling it.

Generic suggested steps, not from the source.

Evidence

First-hand Reddit post with the target star, period, size estimate and a public evidence page (kuber.studio/planethunt) showing the folded light curve and held-back data checks. Different person, star and agent from entry #60

Source: Reddit · 2026-10-18 · Verified by us: not yet · Report broken or outdated

Related use cases

ResearchReddit

Schedule Reddit, email and Search Console digests

Isolated cron jobs scan Reddit, check inboxes, and pull Google Search Console data, then send summaries to Telegram.

  • Level Beginner
  • Setup~20 min per job (source)
  • Evidence Strong evidence
OpenClawSource-linkedBeginner-friendly
ResearchX · 2026-10

Scrape X bookmarks into a Notion database every few hours

Bookmarks pile up and get forgotten. Jeston Lu built a Grok Bot that scrapes saved X posts every 6 hours and auto-categorizes them into a Notion database so the archive stays searchable.

  • Level Intermediate
  • Setup1–3 hrs*
  • Evidence Strong evidence
Grok BotSource-linked
ResearchReddit · 2026-10

"Eternal Star / We Hope So": Claude Decoded Super Mario 64's Unreadable 32x32 Courtyard Plaque After 30 Years

The plaque in Super Mario 64's castle courtyard is a 32x32-pixel texture fans have argued about since the 1990s. No upscaler can read it. Claude built a model of how a 1996 artist likely made it (font, canvas, resize, blur, stone), searched fonts, sizes and words on a GPU, and tested the method on fake plaques with known text. Its best reading: "Eternal Star / We hope so" in Palatino Bold Italic. Code and a 40-page report are public.

  • Level Advanced
  • Setup1–3 hrs*
  • Evidence Strong evidence
ClaudeSource-linked