new-term-radar

中文说明

A daily report of the names that are starting to surge in AI: new models, products, tools and repos, caught where they are said first, before they show up in keyword tools.

Built for people who make pages, posts or products around new terms: SEO for AI tool sites, newsletters, directories, anyone who wants to know about "Strata" or "Seedance" the day it appears and not two weeks later.

Why

A new name leaves a trail, in this order:

1. A lab or a well-followed account says it on X; a model enters Hugging Face's trending list.
2. One GitHub repo takes off on its own.
3. Directories and competitors add pages for it; someone registers a domain for it and the site starts to rank.
4. Your own site gets its first search impressions for it.
5. Google Trends shows the curve, days or weeks later.

Keyword tools read step 5. This radar reads steps 1 to 4 every day and uses step 5 only to check itself.

One example it was built around: Niko1221/Strata was created on 2026-09-24 and had 7,700 stars nine days later. People were searching "niko strata" from 9/26, while no second repo carried the name and no keyword tool listed it. A single repo gaining 800 stars a day is the whole signal, and it is public.

What it reads

Signal	What it catches	Needs	Cost
① X	Names the accounts in your list used for the first time in 60 days	AIsa key	$0.003 per account per run
① Hugging Face	Models new to the trending top 50; quantised copies grouped under the base name	nothing	free
② GitHub breakout	A repo under 14 days old averaging 200+ stars a day, or +400 since yesterday; adds the search variants people use ("niko strata")	nothing (a GitHub token raises the rate limit)	free
③ Sitemaps	Words that several new URLs on a site share and its older URLs rarely carried	the sitemaps you list	free
③ New sites	Domains registered and first indexed in the last 90 days that already rank for 20+ keywords	AIsa key	about $0.13 per query, weekly
④ Search Console	Queries your site got impressions for, for the first time (fresh data)	your own Google token	free
⑤ Review	Each lead checked in Google Trends 14 days later, against its own baseline; hit rate and days ahead per signal	AIsa key	$0.0012 per search variant
Keyword table	For the day's new names: the generic search terms behind them (what people do with the new thing), each sized and given a decision	AIsa key; GoAnyAPI key optional	about $0.15 a day for 5 names, $0.22 with GoAnyAPI
Name judge	A small model scores every term: the name of one specific thing, or a common word?	AIsa key	a fraction of a cent per run

Prices are what AIsa charged in October 2026. With the example config (35 X accounts read three times a day, the keyword table for 5 names a day) a month costs about $15: $10 for the X reads, $5 for the keyword table. Read fewer accounts, or read them once a day, and it drops in proportion.

The keyword table

A name is half of what you need. "SynthID Detector" has a short life as a keyword and belongs to Google; the job it does, "ai image detector", is what people keep searching, and nobody owns it. Each day the radar reads the new names once more and writes one table with both:

| Keyword | Type | Behind | New? | Est. searches/day | Started rising | Peak vs gpts | Peak day | Last 7 days vs the 7 before | Now | Decision |
| **photocraft** | name | — | yes | 12747 | 2026-10-05 | 97 vs 3.1 | 2026-10-09 | — | still rising | **prioritize** |
| **claude haiku 5.5** | name | — | yes | 1863 | 2026-10-07 | 100 vs 23.7 | 2026-10-08 | ×6.0 | still rising | **prioritize** |
| **ai image detector** | generic | synthid detector | no | 2537 | — | 87 vs 31.6 | 2026-10-04 | ×1.2 | flat | watch |
| **photoshop alternative** ⚠ | generic | photocraft | no | 244 | — | 61 vs 61.7 | 2026-10-08 | ×1.8 | flat | skip |

(a real run, 2026-10-12, shortened)

How it is made (radar/usecases.py):

1. Evidence: the most-liked posts that mention the name (X advanced search) and, for a repository, its README.
2. Phrases: a model reads the evidence and writes the keyword an ordinary person would type for each job it sees people doing, with a quote that backs it. A phrase built on another product's name ("photoshop alternative") is kept and marked ⚠: demand often hangs on the incumbent, and whether to use someone's brand is your call. With a GoAnyAPI key (optional, below) the radar also takes Google Trends' related queries for the name: what people really searched together with it. For SynthID Detector that gave "ai photo detector", "google ai detector" and "ai detector"; these rows carry 🔎. Queries that hold the name are listed as its long-tails ("photocraft download", "nano banana 2.1 vs pro"). Queries that are themselves the names of other rising things ("gpt image 2.5" beside "nano banana 2.1") are kept as leads of their own.
3. Screen: a second call scores how well the name answers each phrase, marks brands, and spots the names of other things; the loosely related ones are dropped. For Claude Haiku 5.5 it dropped all six proposed ("ai coding assistant", "github copilot alternative"); for SynthID Detector it kept all five.
4. Volume: Google Ads monthly searches for the rest, one batch call. Phrases under min_volume are dropped; most are.
5. Trends, twice per row: the term alone gives the shape (new or not, the day it started rising, the peak, the last week against the week before, what it is doing now); the term beside a benchmark keyword (gpts by default) gives the size.

Searches a day are estimates. A generic term's come from its own Google Ads volume, moved to today along its own Trends curve. The benchmark is then sized from those terms, and a name, which has no volume data yet, is sized against the benchmark.

Decision: **p