roman engagement report
@Nozelcode - 209K followers on X
Measured over 18 original posts from a 30-day window, last computed on October 6, 2026.
Engagement
A typical post picks up 588 interactions against 209K followers, an engagement rate of 0.282%. Measured over 18 original posts, its engagement rate beats 77% of 20,444 tracked accounts of a similar size. Comparing inside a size band matters here: engagement rate falls as accounts grow, so a raw rate would mostly just re-measure the follower count. Posts are seen about 202K times each, and 0.292% of those impressions turn into an interaction. That is about 96.4% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 4.3 posts a day over the last 30 days, with activity on roughly 50% of days. Most posts go out around 12:00 UTC, and Friday is the busiest day of the week. Of the 18 posts sampled, 78% carry an image or video, 11% are part of a thread and 39% link out. The account's strongest tracked post pulled 3.8K interactions, about 6.5x its own typical post.
Measured over 18 original posts from a 30-day window, last computed on October 6, 2026.
Compared with accounts its own size
roman's engagement rate beats 77% of the tracked X accounts closest to it in follower count (20,444 accounts, accounts of similar size (decile 9 of 10)). A percentile is spread evenly by construction, so 50 really is the middle of that group and 90 really is its top tenth.
On engagement per impression rather than per follower it beats 17% of the same group. When those two numbers disagree, the gap is about how far its posts travel rather than how people react to them.
Where this sits in the catalog
At 0.282%, roman sits above the 50th percentile of the 204,956 accounts in this comparison. That places it in the above the median band, which runs 0.143% to 0.678%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.024% |
| 50th percentile | 0.143% |
| 75th percentile | 0.678% |
| 90th percentile | 2.55% |
| 99th percentile | 82.4% |
This ruler is the whole measured catalog, not a size-matched group: it shows where the raw rate falls across every account we can measure, all of which are large. For a like-for-like comparison, read the size-band percentile above instead. See how the bands are built
Posting timing
This account posts most often around 12:00 UTC, and Friday is its busiest day of the week. The bars below are the catalog-wide pattern, with this account's own busiest slot marked. They do not show how this account performs at each hour: we keep one aggregate per account, not one per hour, so that measurement does not exist in our data.
Show engagement by hour posted, utc as a table
| Hour (UTC) | Vs author median | Posts |
|---|---|---|
| 00:00 UTC | -1% | 89K |
| 01:00 UTC | -2% | 90K |
| 02:00 UTC | -3% | 88K |
| 03:00 UTC | -4% | 94K |
| 04:00 UTC | -5% | 76K |
| 05:00 UTC | -4% | 75K |
| 06:00 UTC | -5% | 86K |
| 07:00 UTC | -5% | 93K |
| 08:00 UTC | -4% | 108K |
| 09:00 UTC | -4% | 124K |
| 10:00 UTC | -3% | 129K |
| 11:00 UTC | -3% | 141K |
| 12:00 UTC | -3% | 154K |
| 13:00 UTC | -3% | 167K |
| 14:00 UTC | -4% | 173K |
| 15:00 UTC | -2% | 176K |
| 16:00 UTC | -3% | 171K |
| 17:00 UTC | -3% | 159K |
| 18:00 UTC | -2% | 149K |
| 19:00 UTC | -2% | 141K |
| 20:00 UTC | -1% | 131K |
| 21:00 UTC | 0% | 116K |
| 22:00 UTC | -2% | 100K |
| 23:00 UTC | -1% | 90K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +5% | 393K |
| Monday | +1% | 483K |
| Tuesday | -2% | 520K |
| Wednesday | -3% | 472K |
| Thursday | -2% | 430K |
| Friday | -3% | 447K |
| Saturday | +2% | 393K |
Formats this account uses
Its own posting mix on the left, and what each of those formats does across every account we track on the right. Only formats where the effect clears our publish test appear here, so an empty row is a format we could not measure rather than one that does nothing.
| Format | This account | Catalog effect | 95% interval | Accounts behind it |
|---|---|---|---|---|
| Image or video | 78% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 39% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 78% of this account's sampled posts carry an image or video. Across the catalog, posts with an image or video run 111% above the same accounts' other posts.
- 39% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts.
- Its average post runs 398 characters, which falls in the over 280 characters band. Across the catalog, posts over 280 characters run 15% above the same accounts' other posts.
These are catalog-wide differences applied to this account's own posting mix, not a measurement of how each format performs for this account specifically. We keep one median per account, not one per format per account, so the second thing is not something this data can tell you.
Best tweets
- Sep 9, 20266.5x their median
Introducing the largest Meta ads dataset, ever. Over 3 million ads analyzed... yesterday Ask Lightreel: "Find me all Granola paid influencers" "What do good street interviews do?" "Write better hooks for my ads" Try it for free! (PS — Every pixel in this video is a Meta ad)
- Oct 1, 20263.9x their median
CREARON UN CAPCUT GRATIS Y SIN MARCAS DE AGUA, Y YA TIENE 76K STARS EN GITHUB CapCut te pone marca de agua, te bloquea funciones y encima te cobra una suscripción. Un grupo de devs se cansó y construyó la alternativa open source. Se llama OpenCut. Un editor de vídeo con arquitectura basada en plugins, pensado para ser el CapCut real, pero abierto. Sin marcas de agua. Sin paywalls. Sin suscripciones. Lo que incluye: → Editor completo con línea de tiempo y multipista → Plugins nativos para ampliar lo que puede hacer → Una sola app para web, escritorio y móvil → MCP Server, automatizaciones y soporte para agentes de IA → Licencia MIT: puedes hacer lo que quieras con él Instalarlo es muy fácil: → Clona el repo desde GitHub → Instala las dependencias → Ejecuta la versión clásica, que ya está disponible → Sigue la nueva versión en https://t.co/4g6FSS8a8v Es exactamente lo que CapCut debería haber sido desde el principio. Te dejo el repo en comentarios 👇
- Oct 2, 20262.9x their median
Anthropic ha publicado un taller sobre cómo construir una empresa solo con Agentes IA. Agentes trabajando entre ellos, repartiéndose tareas y ejecutando procesos. Gratis. Del equipo que creó Claude. Lo he subtitulado al español. Si quieres que la IA trabaje por ti, guarda esto 🔖
- May 11, 20263.5x their median
https://t.co/h4lxT0CH4L
- Oct 4, 20261.7x their median
🚨 ESTO NO SE LO ESPERABA NADIE Jack Dorsey, ex-CEO de Twitter, acaba de publicar gratis un framework completo para construir un negocio operado íntegramente por agentes de IA. El proyecto ya ha superado las 35.000 estrellas en GitHub. Cómo ponerlo en marcha en unos 5 minutos: 1. Clona el repositorio. 2. Levanta tu propio servidor desde el que podrás gestionar canales, búsqueda, Git y automatizaciones. 3. Incorpora tu agente a cualquier canal como si fuera otro miembro del equipo, asigna sus permisos y trabaja con él en tiempo real. Guarda este post porque probablemente vas a necesitar volver a él. Te dejo el repositorio abajo 👇
- Sep 11, 20261.7x their median
🚨 Ahora puedes convertir cualquier libro en una skill de Claude. Normalmente, utilizar un libro completo como contexto puede consumir cientos de miles de tokens antes de hacer una sola pregunta. Alguien acaba de crear una herramienta open-source para solucionar este problema. Se llama book-to-skill y transforma cualquier libro en una skill que Claude puede consultar capítulo por capítulo. Esto es lo que genera: → Un archivo SKILL.md con los conceptos principales y el índice completo → Un archivo independiente por cada capítulo → Un glosario con los términos clave y sus referencias → Un documento con todas las técnicas, patrones y algoritmos del libro → Una guía rápida con reglas y tablas de decisión Lo más interesante: Los capítulos solo se cargan cuando realmente los necesitas. Puedes instalar 20 libros y Claude únicamente consume tokens del capítulo que estás consultando en ese momento. Un libro de 400 páginas puede requerir alrededor de 200.000 tokens si lo cargas completo. Con este sistema, cada respuesta se basa directamente en el contenido del libro y reduces gran parte de las alucinaciones. Es completamente gratuito y open-source. Te dejo el repo en comentarios 👇
- Sep 29, 2026
UN INGENIERO DE ANTHROPIC ACABA DE SOLTAR EL MEJOR TRUCO PARA OPUS 5.5 Abre Claude Code y escribe: /claude-api prompt-audit → Audita tus skills, CLAUDE.md y prompts → Borra todo lo que frena al modelo → Lo reescribe con la guía oficial de Opus 5.5 Tus prompts están escritos para modelos viejos. Esto lo arregla en 5 minutos. Guárdalo. Por: @RLanceMartin
- Oct 1, 2026
Today we're launching Financial Modeling Autopilot. It's the first AI that operationalizes financial modeling across your entire book of coverage. Autopilot builds and updates models the way you would, fully in the background, and in a way you can fully trust.
- Sep 10, 2026
we’re finally launching https://t.co/aZoUDTlZ8W on YC! most apps were designed for people, not for agents @Okibi_ai turns your product into a CLI, so AI agents can use it just like your users do. https://t.co/WWp3sT1GVQ
- Sep 18, 2026
JUST IN: Bank of America declares investors should prepare for the risk that the Fed raises rates “above 5%.”
Ranked by total interactions across everything we have tracked for this account, which is a longer history than the 30-day window the rates above use. The multiple compares each post to this account's own median.
Buy or sell Twitter (X) accounts - escrow-protected
PlayerSells is an escrow marketplace for Twitter (X) accounts. Every deal is protected, with no middleman risk.
Reading these numbers
A typical post picks up 588 interactions against 209K followers, an engagement rate of 0.282%. Measured over 18 original posts, its engagement rate beats 77% of 20,444 tracked accounts of a similar size. Comparing inside a size band matters here: engagement rate falls as accounts grow, so a raw rate would mostly just re-measure the follower count. Posts are seen about 202K times each, and 0.292% of those impressions turn into an interaction. That is about 96.4% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 4.3 posts a day over the last 30 days, with activity on roughly 50% of days. Most posts go out around 12:00 UTC, and Friday is the busiest day of the week. Of the 18 posts sampled, 78% carry an image or video, 11% are part of a thread and 39% link out. The account's strongest tracked post pulled 3.8K interactions, about 6.5x its own typical post.
- What is roman's engagement rate on X?
- roman (@Nozelcode) has an engagement rate of 0.282%, based on the median interactions across 18 original posts from the last 30 days against 209,056 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.282%, roman sits above the 50th percentile of the 204,956 accounts in this comparison. Those comparison accounts are all large ones, because our scanning cadence is weighted towards big accounts, so this is a ranking among peers of similar scale rather than a ranking across X.
- Does @Nozelcode have real engagement?
- Its engagement rate beats 77% of the tracked X accounts closest to it in follower count (20,444 accounts), which puts it in the top quarter for its size group. Ranking inside a size band matters because engagement rate falls as accounts grow, so a raw rate would mostly re-measure the follower count. It is a starting point for a look at follower quality, not a verdict on it.
- When does @Nozelcode post?
- Most posts go out around 12:00 UTC, and Friday is its busiest day, at roughly 4.33 posts per day across the measured window.