zhuyansen/new-term-radar

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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, each new one with the first words it ranks for in Google's top 20, in any country: searches a site that new already reached	AIsa key	about $0.13 per query, weekly; about $0.013 a new site for its words
⑦ Asks	What people ask for on Reddit ("is there an AI tool that…", twelve phrasings), X, Stack Exchange (Software Recommendations and three more) and Freelancer.com: 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, plus a few cents for X
⑧ Sellers	Sites that just put up their first payment link (Stripe Payment Links, Polar, Lemon Squeezy, Gumroad, Creem, Paddle, Dodo Payments, Waffo Pancake), from the public link graph with the day each site first linked; new pages of old sellers, platform pages, forums and one link shared by several new sites (a network's) left out; the site's own description goes to the keyword table, and with GoAnyAPI its visits, its domain's registration and where its visitors come from (the AI share)	AIsa key; GoAnyAPI optional	about $0.50 a week
⑧b Builders	Sites just built with Lovable or v0 and newsletters just started on beehiiv, read off their badges; only the software among them becomes a lead	AIsa key	about $0.15 a week
⑨ Just listed	New on Product Hunt, Show HN, OpenRouter, Civitai, the App Store's top-grossing charts and awesome lists (free); weekly, the pages Google indexed under Figma plugins, There's An AI For That and the Chrome Web Store, trending searches on Douyin, TikTok and Reddit, and rising searches next to root words ("ai generator")	nothing for the free lists; AIsa and GoAnyAPI keys for the rest	free; about $0.02 a path, $0.001 a trending list, 6 GoAnyAPI credits a root word
⑩ Money	The other sites on a paying tool site's AdSense account (its owner's other niches), and the advertisers new on your own terms (Google Ads Transparency)	GoAnyAPI key	3 credits a site each way, 4 a term; weekly
Beside the names	For the day's strongest new names: new domains carrying the name (whois, or crt.sh certificates), Wikipedia views, what Google knows it as, Discord servers; for paying products, the "alternative", "vs", "free", "pricing" and "review" searches	AIsa key; GoAnyAPI for Discord	about $0.12 a name read by whois, $0.09 for the searches
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 DataForSEO 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

What happens	What the table loses	The line it prints
No `GOANYAPI_API_KEY` (the default)	The 🔎 rows, each name's long-tails, the other names searched alongside, and the `(US)` readings. Phrases come from the model alone and every curve from the worldwide series, where a real move can read flat	"Related queries are off: set GOANYAPI_API_KEY…"
GoAnyAPI's Trends is down (seen on its first day in use, 2026-10-12)	The same as having no key, for that run	"Related queries failed for: …" and "Country series failed, worldwide data used instead: …"
AIsa's post search fails for a name (timeouts seen twice on 2026-10-13)	That name's posts. A repository still has its README; a model or product without one is left with the related queries only, and with no GoAnyAPI key it gets no generic terms that day	"The post search failed; this run used READMEs and related queries only: …"
Neither posts nor a README for a name	Its generic terms; the name's own row stays	"No posts or README found for: …"
No lead that day is a thing with a name score of 0.8 or more	The whole table	"Nothing to read today…"
AIsa's search-volume or Trends lookup fails	The whole table: these two are not replaceable	the error, in place of the table

Platform	Counted from	Sites since 2019	New sites a month, May to September 2026	Linking today
Stripe	June 2021 (a few dozen a month before)	306,000	6,500 to 8,200 (14,200 in June)	143,000
Gumroad	2019	530,000	4,200 to 5,700, while 6,400 to 9,400 drop their links	140,000
Lemon Squeezy	2023	34,000	600 to 1,100	18,000
Polar	2024	2,285	109 to 268	1,943
Creem	2025	1,708	74 to 268	1,449

Key	What it is
`lang`	`"en"` or `"zh"`: the language of the report
`x_accounts`	`labs` and `bloggers`: X handles to read. Labs say names first; pick the bloggers your field's new terms spread through
`sitemaps`	Sites whose new pages you want to see. `index` is a sitemap, or a sitemap index when `shards` (a regex) picks which sub-sitemaps to read. `pause` is the seconds between requests to that site. `strip_locale` drops `/en/`, `/zh-CN/` prefixes so one entry in many languages counts once
`topics`	Name and regex: each topic gets its own section listing the leads, repos and queries that match
`known_terms`	Terms you already have a page for, or never want reported. A lead that contains one, or is contained in one, is marked and not kept for review
`stop_words`	Everyday words of your field, added to the built-in list (which is tuned for AI tooling)
`judge`	`model` (any chat model on AIsa) and `min_score` (0.5)
`breakout`	`window_days`, `min_stars`, `velocity_min` (stars a day), `delta_min` (stars since yesterday)
`new_sites`	`queries`: a name and a SQL LIKE pattern on the domain (`"%ai%"`), one paid query each; `weekday` (0 = Monday)
`review`	`after_days` (14) and `per_day` (5 leads a day)
`usecases`	The keyword table. `per_day` (names read a day, 0 = off), `model`, `benchmark` (the keyword sizes are compared with), `min_volume` (monthly searches a phrase needs), `min_daily` (searches a day for "prioritize"), `recheck_days` (3), `related` (use related queries when `GOANYAPI_API_KEY` is set), `related_geo` (`US`), `country_trends` (read the bigger rows' curves from that country), `country_min_volume` (1000) and `country_max` (8)
`word_age`	`enabled`, `time_range` (`past_5_years`, the longest the Trends source offers), `new_days` (180: first searched within this many days = 🆕, read one step easier on page one)
`markets`	`enabled`, `codes` (`["US", "DE", "FR", "JP"]`; built in: US, GB, CA, AU, IN, DE, FR, ES, IT, NL, BR, JP, KR), `difficulty` (per-market keyword difficulty), `top_region` (the Trends top country), `locations` (more markets: `{"MX": [2484, "es"]}`, a Google Ads location code and a language)
`serp_shape`	`enabled`, `location_code` (2840), `language_code` (`en`), `device` (`desktop`), `platforms` (domains that count as high-authority platforms; `*.github.io` means its subdomains)
`yours`	`enabled`, `domains` (your sites; empty = the Search Console property's domain), `days` (28: the Search Console window)
`year_curve`	`enabled`: the twelve-month column, from the volume call (free)
`dot_com`	`enabled`, `max_rows` (8: prioritized rows checked a run, names first)
`ai_answers`	`enabled` (`false`: it costs about $0.004 an answer), `engines` (`["chatgpt"]`; add `"google"` for AI Mode), `max_rows` (6), `prompt` (`"What is the best tool to {job}?"`), `location_code` (2840), `language_code` (`en`)
`gsc`	`site` (`sc-domain:example.com`) and `token_file`. Leave `{}` to turn the signal off; with it set, `yours` also reads your average position per keyword

Skill	What it does
`new-term-radar`	The whole run: today's new names, then the keyword priority table for them. Also takes names you already have. Start here
`ai-listening`	Collects what is new in the last 24 hours across the signals, deduplicated, as one report of names
`seo-new-keywords-research`	Takes names, or raw text that mentions them, and returns the keyword priority table: the generic terms behind each name, screened, sized and given a decision

zhuyansen/new-term-radar

new-term-radar

Why

What it reads

The keyword table

When a source is missing or down

⑥ Revenue: what people already pay for

⑦ Asks: demand said out loud

⑧ Sellers: who just started taking money

History: every seller back to 2019

⑧b, ⑨, ⑩ and the evidence beside the names

⚡ What tutorial viewers ask for

Pain points: `python -m radar pains "ai headshot"`

One key, and an optional second

Quick start

What a report looks like

config.json

Search Console (optional)

Mail (optional)

Use it from an agent: skills and an MCP server

Skills

MCP server

Codex, TRAE, WorkBuddy and DeepSeek Harness

Run it on GitHub Actions

How the pieces decide

What we measured, and what we have not

Known issues

Development

Thanks

Star history

License

Tool	What it returns	Cost and time
`recent_leads`	What the radar kept, with review verdicts and the hit rate per signal	free, instant
`keyword_table`	The keyword table for names you give it	about $0.05 a name plus $0.09 a call; 40 to 90 seconds a name
`run_radar`	One `sources` or `daily` run and its report	paid; minutes. For a first try: the schedule belongs in cron or Actions

new-term-radar

Why

What it reads

The keyword table

When a source is missing or down

⑥ Revenue: what people already pay for

⑦ Asks: demand said out loud

⑧ Sellers: who just started taking money

History: every seller back to 2019

⑧b, ⑨, ⑩ and the evidence beside the names

⚡ What tutorial viewers ask for

Pain points: python -m radar pains "ai headshot"

One key, and an optional second

Quick start

What a report looks like

config.json

Search Console (optional)

Mail (optional)

Use it from an agent: skills and an MCP server

Skills

MCP server

Codex, TRAE, WorkBuddy and DeepSeek Harness

Run it on GitHub Actions

How the pieces decide

What we measured, and what we have not

Known issues

Development

Thanks

Star history

License

Pain points: `python -m radar pains "ai headshot"`