<div align="center"> <img src="docs/logo.svg" width="128" alt="new-term-radar logo: a radar sweep catching a new blip">

new-term-radar

Catch the names AI people are about to search for, the day they appear, before keyword tools list them.

⭐ 700+ stars on its first day, 1,000 in just over three · on PyPI, the official MCP Registry, Cursor Directory, LobeHub, Tessl, ClawHub and skills.sh

Quick start · What it reads · The keyword table · Agents and MCP · config.json · 中文说明

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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

Purple, tagged NEW: what 0.3 to 0.5 added (⑥ revenue, ⑦ Reddit asks, ⑧ sellers, the page-one check, the format and ⚡ marks, the pains command).

| 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 and Spaces (the demos people try) new to the trending top 50; quantised copies and a model's own demo 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 example config watches eight AI tool directories (toolify, aixploria, ai-bot.cn, opentools, dang.ai, clipfly, aitoptools, futurepedia) and four MCP and skill directories | 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 | | ⑦ Asks | What people ask for on Reddit ("is there an AI tool that…", twelve phrasings): a model keeps the requests and complaints an AI tool could answer and writes each job as people would search it; jobs with searches get the page-one check | AIsa key | about $0.12 a week | | ⑧ Sellers | Sites that just put up their first payment link (Stripe Payment Links, Polar, Lemon Squeezy, Gumroad, Creem), from the public link graph with the day each site first linked; new pages of old sellers, platform pages and forum threads left out; the site's own description goes to the keyword table | AIsa key; GoAnyAPI optional, for visits | about $0.40 a week | | ⑥ Revenue | Products people pay for, from TrustMRR's verified revenue: the fastest growing ($500+ in 30 days) and the newest listings; one at $0 last time and earning now is called out first. Its own description goes to the keyword table as evidence | TrustMRR key | free, 6 requests, 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, checked for room on page one, and given a decision | AIsa key; GoAnyAPI key optional | about $0.18 a day for 5 names, $0.30 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 | Page one | 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; the Page one column came later, see below)

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.
6. Page one, for the rows that would be acted on (eight at most): Google's first page (about $0.002 a keyword), the rating of each site on it (GoAnyAPI, $0.002 a site, kept 30 days) and the keyword difficulty ($0.012 a call). With a GoAnyAPI key also who already builds for the term and who pays for it: the pages Google holds with it in the title from the last month (pages built) and the domains running Google ads on it (advertisers, from Ads transparency), $0.008 a row. open = three or more of the ten results sit on sites rated under 30, or difficulty under 20; crowded = none does and difficulty is 40 or more; mixed in between. Under the table it names the weakest site on page one, where a new page can get in, and what kinds of pages hold it (tools, lists, articles, videos, forums). Ads on the page mean someone pays for that click.

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: prioritize = rose in the last 30 days, still up, at least min_daily searches a day. watch = rose but smaller, too early to read, or flat with steady demand of that size. skip = fading, or flat and small. A prioritize whose page one is crowded becomes watch ↓: still rising, but page one belongs to strong sites. In a name's first week page one is still forming (news, the maker's own pages); the second reading three days later is the one to trust.

Marks: 🎬 video, 🎙 voice, 🖼 image says what the thing makes, the usual order of what visitors pay for (video > voice > image > text); leads of equal standing are sorted by it. ⚡ = a post with 1,000 or more likes walks through a manual workflow or rides a trend: a one-click tool nobody has built yet. Both come from keyword rules over the lead's own words and posts; on six known names (Nano Banana, Veo 3.1, Seedance 2.5, Claude O