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One developer measured 7,032 plugins in the WordPress.org directory. Phase one of search is a hard keyword filter; phase two is ranked partly on installs a new plugin does not have.
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A developer shipped a plugin to the WordPress.org directory, got zero installs, and then queried the free, keyless directory API to work out whether the fault was his listing or the system [1]. His count: roughly 19% of plugins in the directory never pass zero installs, more than 10,500 of them, which implies a directory of about 55,000 [2][3].
The mechanism is documented rather than mysterious. The best-documented account traces to WP Tavern's 2017 coverage of the directory relaunch, quoting Greg Brown, the Automattic data engineer who built it: search runs on Elasticsearch in two phases [4]. Phase one builds a candidate pool by matching against title, excerpt, description, tags, slug, author name and contributor names [5]. Every keyword in the user's query has to appear somewhere in that set, or the plugin is excluded from the result set entirely, not ranked low [6]. Phase two then sorts the survivors by last update date, compatibility with the current core version, active installs, percentage of support tickets resolved, and average rating [7].
That split is the whole practical finding, because it separates two failures that look the same from outside. On the author's own live plugin, the query "spam registration" returns nothing because the word "spam" appears nowhere in the listing; that is a phase-one exclusion and free to fix [8]. The query "email validation" fails even though every word is present, because the term is held by WP Mail SMTP and CleanTalk on install count, and no amount of rewriting moves it [9]. One is a typo-grade defect in copy. The other is not a copy problem at all.
The distribution data is bleaker. Sweeping the directory for plugins with 1,000 or more active installs returns 7,032; filtering to those added in the last 18 months leaves 167 [10][11], about 2.4% of the set [12]. Of those 167 breakouts, 88% had some pre-existing distribution [13]. One vendor launched eight of them off the back of a two million install plugin, another launched three off ten million [14]. Part of the remainder looks like cold starts only because the authors have no other WordPress plugins: the author names Visa, Sendcloud and a hosting company, businesses shipping an integration to customers they already had somewhere else [15]. Digging into what was left, he reports two out of sixty-nine surviving as genuine unknown-author cold starts [16]. Note that 12% of 167 is about 20, not 69, and the article does not reconcile the two denominators [17].
The two survivors are instructive in opposite directions. One is a floating WhatsApp button from an author with a single plugin and no brand, serving a very common low-friction search intent that directory search surfaces well [18]. The other is an llms.txt generator, which broke out because llms.txt did not exist before 2025, so no incumbent had an install-count advantage [19].
For a plugin at zero, the only levers inside phase two are release cadence and resolving support threads, two of the five ranking inputs and the two that correlate with breaking out from nothing [20].
What to watch: run the documented curl query against your own terms, using the -g flag so the shell does not glob the square brackets, and separate your absent-keyword failures from your install-count failures before rewriting anything [21]. Watch newly coined vocabulary, where incumbency has not formed yet [19]. And treat any confident claim about what makes users click install as guesswork, because WordPress.org gives authors no listing views, impressions or click-through data at all [22].
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Ranked by verification strength, evidence, and original report placement.
Roughly 19% of all plugins in the WordPress.org directory never pass zero installs, which is more than 10,500 of them.
The two behaviours that correlate with breaking out from nothing are release cadence and resolving support threads, which are two of the five phase-two ranking inputs and the only two a plugin with no installs can move.
The author shipped a plugin to the WordPress.org directory, it got zero installs, and instead of reading marketing advice he queried the directory API and counted; the API is free, needs no key, and every query used is published in the article.
The best-documented account of how directory search works traces to WP Tavern's 2017 coverage of the directory relaunch, quoting Greg Brown, the Automattic data engineer who built it; it runs on Elasticsearch and has two phases.
The 19% / 10,500 figures imply a directory of roughly 55,000 plugins.
Phase one builds the candidate pool by matching against title, excerpt, description, tags, slug, author name and contributor names.
Evidence-backed comparisons of source perspectives and observed adoption signals. Read the methodology
Which Builder, Operator, and Investor concerns the observed source mix emphasized—not a truth score.
Evidence, demonstrated adoption, hype gap, incentives, and confidence are assessed independently, each on its own current evidence. How these are measured.
Reproducible method, single unverified source
The strongest element is method transparency: the queries run against a free public API are printed, so the counts are in principle checkable by any reader. Against that, everything rests on one self-published post with no independent replication, the search-mechanism description is sourced to 2017 third-party coverage rather than current documentation, and the article contains an arithmetic gap it never reconciles.
Concrete ecosystem counts, no uptake signal for the thesis
There is real quantitative adoption data about the ecosystem the story describes: 7,032 plugins above 1,000 active installs, 167 recent breakouts, a >10,500-plugin zero-install cohort, and release/support behaviour for three named plugins. What is absent is any signal that the article's prescriptions or measurement approach have been picked up by other developers or acknowledged by the platform, and the counts are a single undated-methodology snapshot by one author.
Slightly overstated relative to one dataset
The article is unusually self-limiting for the genre: it flags the missing analytics, labels the readme-length pattern non-causal, and notes the zero-install label really means fewer than 10. Still, a headline structural conclusion about how 'anyone gets their first install' is carried by one unreplicated sweep, a three-plugin behavioural comparison in the author's own category, a 2017 secondhand account of the ranking system, and a cold-start denominator that does not reconcile.
Self-published developer with a plugin in the market analysed
The author is a WordPress plugin developer writing about the discovery system his own zero-install plugin competes in, on a self-publishing developer platform, and the piece names his category and rival plugins. That is a visible interest in the framing, though no vendor sponsorship, paid placement or undisclosed relationship appears in the record, and the method is published in a way that invites checking.
Moderate: mechanism plausible, magnitudes unconfirmed
Confidence is moderate because the mechanism claims are internally coherent, attributed, and checkable via a free API, while the numbers come from a single author with no replication, the ranking description is nearly a decade old, and one key ratio is internally inconsistent. Directional conclusions about phase-one exclusion and install-count incumbency deserve more weight than the precise percentages.
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1 article · August 16, 2026