Foreverse Research · The Character Card Census

A census of 19,776 roleplay cards:
the ecosystem behind 950 million chats

Who lives in this universe, what gets written, what traffic rewards, and what the engineering spec of a hit card looks like. We censused every public card on a Chinese roleplay-card community — aggregates only, no card named, no content reproduced. Snapshot 2026-07-03, updated annually.

19,776 cards, full metadataTop 1,000 dissectedAggregates onlySnapshot 2026-07-03

Snapshot captured 2026-07-03 · Census published 2026-07-26

Four headlines from this census

  1. Traffic is a pyramid: the top 1% of cards (197 of them) absorb 40.3% of all chats, the top 10% absorb 73.4%. Yet the middle is real — the median card still logs 9,873 chats. This is not a winner-take-all wasteland.
  2. 83.0% of characters are male; female characters are 5.5%. It's an audience-of-women universe: the play is “pursue him”, and the top tags — pure-love, jie, position-locked — are community pacts around exactly that.
  3. Every tag where demand outruns supply is a structurally complex card: multi-character (lift 4.22), infinite-loop worlds (3.31), simulators (2.37), system cards (2.22), ensembles (1.90). The most-written mood tags — redemption, secret crush, love at first sight, single-character — are all oversupplied.
  4. A hit card is an engineering artifact: median greeting 1,232 chars of prose, 90% wrapped in HTML, median beautify code 39,189 chars; 73% embed a BGM player, 52% ship collapsible panels, 49% a memory zone. A card stopped being a persona paragraph — it's a miniature front-end project.

The shape: a pyramid with a living middle

First, the question everyone asks: is this a winner-take-all market? It's a pyramid — and the middle is alive. The top 197 cards (1%) absorb 40.3% of all chats, yet the median card still logs 9,873. Not a market of one star and a crowd of extras.

19,776Public cards
950MLifetime chats
4,596Creators
9,995Unique tags

The chat pyramid: who lives on each floor

Five floors by lifetime chats per card. Left wing = that floor's share of all cards; right wing = its share of all chats. The 102 million-chat cards (0.5%) absorb 32.6%; the 10k–100k middle class takes 27.9% with 42.4% of the cards.

Concentration on another scale: the top 10 cards absorb 12.8%, top 100 take 32.4%, the top 1% (197 cards) 40.3%, and the top 10% take 73.4%.

The creator side is even more top-heavy

4,596 creators, 4.3 cards each on average. 39.6% published exactly one card and never returned; at the other end, the most prolific account carries 123.

Chats concentrate toward top creators even harder than toward top cards: 1% of creators absorb 46.2% of all chats. An author brand is worth more than a hit card.

Who lives here: 83% male characters

83.0% of cards are male characters; female characters are 5.5%. Keep that number in hand and everything else clicks — the pact tags (pure-love, jie, position-locked) and the pursuit-style play are the grammar of a women-audience community.

  • Male83%16,412
  • All-gender8.2%1,614
  • Female5.5%1,091
  • Multi-character1.8%360
  • Non-binary0.6%127
  • Non-human0.6%126
  • Custom0.2%46

Gender-code semantics are inferred from the creation form's enum order plus tag co-occurrence (see method); the all-gender and multi-character rows house most ensemble cards.

Character age: a peak at 20, a wall at 18

986 of the top 1,000 declare an age: mode 20, median 21, p90 at 32. Age 18 is the second peak (151 cards); seventeen-and-under is exactly zero — the adulthood line is a hard border here. The small step at 26–28 matches the steady demand for older love interests.

X-axis = declared character age (top-1,000 cards); bars = card counts; gold = the mode, age 20.

Names doubling as shelf labels, covers built for portrait phones

Median name length is 3 Chinese characters — it reads like a person. But 9.8% of names carry a parenthetical edition note, and 7.3% use ensemble notation like “4+1” or “n+1”. The name field is quietly doing shelf-label duty.

75.2% of covers are ultra-vertical art (aspect < 0.6), plus 21.6% ordinary portrait; square-or-wide is 3.2% combined. The portrait phone is this universe's only picture frame.

The tag universe: 9,995 words, a few dozen in circulation

Of 9,995 unique tags, 6,879 were used exactly once — signatures, private memes, one-off declarations. The real shared vocabulary sits in the top few dozen. 67.2% of cards fill all six tag slots (5.49 per card on average); tags are the search surface, and nobody wastes it.

  • Audience & pacts
  • Setting
  • Mechanics
  • Relationship arcs
  • Persona types
  1. 1全性向 all-audience8,314
  2. 2纯爱 pure-love (one pairing only)7,798
  3. 3 jie (exclusivity pact)4,692
  4. 4女性向 for-women4,104
  5. 5架空世界 alternate world3,961
  6. 6校园 campus2,827
  7. 7攻略 pursuit play2,336
  8. 8古风 gufeng (period)2,236
  9. 9群像 ensemble cast2,059
  10. 10限左 position-locked1,943
  11. 11救赎 redemption1,804
  12. 12bg bg (M×F)1,529
  13. 13难攻略 hard-to-win1,346
  14. 14酸涩 bittersweet1,071
  15. 15冷脸萌 cold-face cutie1,059
  16. 16模拟器 simulator1,050
  17. 17同人 fanwork1,002
  18. 18年上 older love interest944
  19. 19单人 single character906
  20. 20gl gl (F×F)870

Top 20 tags by card count, colored by semantic group. Audience-pact words (all-audience, pure-love, jie) own the podium — this universe negotiates terms before genre.

“Jie”: a community pact that grew outside the schema

“Jie” (洁, the exclusivity pact: the character's body and heart have only ever belonged to the player) is declared by 4,692 cards; “not-jie” by 543. That's 8.6 to 1. It isn't a content rating — the platform has no such field, so the community grew one in the tag slots, at a density where staying silent reads as a statement.

A side note: small-town China entered the card universe

Small-town (298 cards), Cantonese (254), Hong-Kong-circle (230), esports (321), band (220) — the aesthetic currents of the recent Chinese internet play out here in real time. Cards are an instant slice of pop culture, with a far shorter reaction arc than long-form fiction.

  • 县城 small-town China298
  • 粤语 Cantonese254
  • 港圈 Hong Kong circle230
  • 电竞 esports321
  • 乐队 band220

Supply vs demand: the gap hides behind the engineering bar

Which lanes are overwritten, which undersupplied? For 59 tags (≥250 cards each) we computed a crowding index, lift: the tag's share of all chats ÷ its share of all cards. Above 1, demand over-rewards the tag; below 1, supply is grinding itself down.

Bar length is log-scaled (lift 4.22 and 0.33 sit roughly symmetric). ◆ = entries cross-checked under a second recipe (top-1,000 occurrence rate ÷ overall rate); every check agrees in direction.

How to read this board

The amplifiers share one trait: multi-character (4.22), infinite-loop worlds (3.31), simulators (2.37), system cards (2.22), ensembles (1.90) — structurally complex cards that ship a play system, not just a person. The red oceans are the mirror image: redemption, secret crush, love at first sight, single-character — mood-heavy tags with a low writing bar and therefore thick supply.

The demand gap sits behind the engineering bar. That is the most practical sentence on this board: to eat an amplifier's traffic, first accept its production cost.

Low lift doesn't mean “don't write it”. The redemption lane holds 1,804 cards and still has million-chat hits — it's a crowding signal, not a quality verdict.

Red packets are creator-side promotion spend: 13.7% of cards carry one, and those cards absorb 22.1% of chats with a median of 15,018 — 1.5× the universe median. Direction can't be settled from a snapshot: packets may buy heat, or confident authors may be the ones who pay. Recorded as is, no causal claim.

The build of a hit card: half writing, half front-end

Dissect the top 1,000 and “writing a card” turns out to be half prose, half engineering. Median greeting: 1,232 characters of pure text (even p25 is 758), 90% wrapped in HTML. Median beautify code: 39,189 characters; the heaviest single card ships 368,517. Only 8 of 1,000 go bare.

Greeting length in pure text (HTML stripped)

The opening-scene kit

  • Timestamp in the opening48%
  • Location line36%
  • Weather line25%

The hit-card opening grammar: timestamp first, then location, then weather — the character enters last.

Panels and play widgets

  • Collapsible panels52%
  • Memory zone49%
  • Affection meter19%
  • Social feed sim15%
  • IM inbox sim14%
  • Group-chat sim13%
  • Live-stream overlay7%

Memory zones at 49% deserve their own line: they're the community's folk-engineering answer to “the model forgets”, and they're nearly a default part now.

The beautify-code layer

  • Chinese webfont82%
  • Embedded BGM player73%
  • Fixed overlay widget64%
  • Full HTML page51%

For 51% of hit cards, the beautify code is a complete HTML page in its own right.

Manual culture: creator notes read like product docs

Across all 19,776 cards, 33.1% of creator notes ship a $-command list, 31.7% discuss model choice, 25.6% carry do-not clauses; median length 191 characters. Players have been trained to read the manual before chatting — your creator notes will be read as product documentation.

This universe has no lorebook

The attachment field is empty on all 1,000 top-card payloads: the platform has no separate lorebook, so lore lives in greeting panels, creator notes and hidden prompts. Against Tavern-style formats (character_book in the v2/v3 spec) that's a different engineering culture — and exactly where content gets lost when cards migrate. To see what your own card carries or drops, run it through our card checkup and lore-trigger simulator. Card checkup → Lore-trigger simulator →

The average card: a dossier of a card that doesn't exist

Stitch every median and mode together and you get this “average card”. No such card exists — but every line of the dossier is a real majority.

Synthetic specimen · no such card

Gender
male (83.0% of cards)
Age
20 (top-1k mode; median 21)
Name
3 characters long
Cover
ultra-vertical art (75.2%)
Tags
all 6 slots filled (like 67.2% of cards)
Tagline
15 characters
Creator notes
191 chars; 1 in 3 ships a $-command list
Greeting
1,232 chars of prose, 90% odds wrapped in HTML
First screen
≈50% odds of a timestamp and a collapsible panel
Lifetime chats
9,873; 53 likes

Six takeaways creators can copy straight into decisions

  1. The red-ocean trio: enter with careSingle-character (lift 0.33), secret crush (0.42) and redemption (0.54) are the three most oversupplied lanes. Not unwritable — just the most crowded, thinnest average returns, sharpest differentiation required.Back to the board
  2. Structure is the biggest open slotMulti-character, simulators, system cards and infinite-loop worlds all run 2×+ over supply. The bar is engineering, not prose — which is exactly why the gap persists. A first step: bolt a progressing status panel onto a single-character card.Card studio
  3. Don't open under 800 charactersThe top-1,000 p25 is 758; the median 1,232. The convention is to perform what's happening right now — 48% open with a timestamp, 36% with a location. Preview your first screen before shipping.Greeting preview
  4. Memory design isn't decoration49% of hit cards build in a memory panel — the community's self-rescue from long-chat amnesia. Treat “what should be remembered” as a field you design, not something the model improvises.Card checkup
  5. Tag slots are free search surface67.2% of cards fill all six. Copy that — and keep at least one slot for a mechanic word (pursuit / simulator / sandbox). The board shows mechanic words carry traffic; pure mood words don't.Back to the tags
  6. Write creator notes as product docsA third of creators list commands; three in ten give model advice. Readers expect a manual: recommended model, boundary declarations, command usage — that's the passing grade here.Our card-writing guide

Method and boundaries

Sample and capture: the full public listing (19,776 cards) of a Chinese mobile roleplay-card community (Mufy), captured 2026-07-03 from public pages in a logged-in browser session; the top 1,000 by lifetime chats got detail captures. Selection verified: the detail set coincides 1000/1000 with the top 1,000 by chats.

Single-platform boundary: this is one platform's cross-section — a Chinese, mobile-first, women-audience-dominant ecosystem. It does not extrapolate to English communities (different card formats, lorebooks, demographics), nor does it equal “the whole Chinese card universe”.

Aggregation discipline: aggregates only. No card content reproduced, no card or creator named, no download channel provided.

Recomputable recipes: every number on this page comes from one stats script. Lift covers the 59 tags with ≥250 cards; greeting length = characters after stripping HTML tags and whitespace; “chats” is the platform's displayed lifetime counter, whose internal definition we cannot audit — all ratios compare within the same recipe only.

Gender codes are inferred: semantics come from the creation form's enum order, verified by tag co-occurrence (code 4's top tag is “non-human”; code 6's names are dense with “27-person”, “4+1”). Not official documentation — cite as inference.

A snapshot, not a trend: the data carries update times but no creation times, so this page makes no growth-rate claims. Trend comparisons start when the next annual snapshot lands.

Four unusable fields: the public API's NSFW / original-character / AI-generated / image-gen flags are false on every card (unset or filtered platform-side); this page never cites them.

Changelog

The yearbook commitment: every new snapshot lands here, old numbers stay for side-by-side reading.

  1. 2026-07-26First census: 19,776-card metadata + top-1,000 details, snapshot 2026-07-03. Annual commitment: the next snapshot lands as a side-by-side update — old numbers stay.

FAQ

Where does the data come from? Does it hurt creators?

The sample is the public listing metadata of 19,776 cards on Mufy, a Chinese mobile roleplay-card platform, captured 2026-07-03 from public pages in a logged-in browser session; the top 1,000 by lifetime chats got detail-page captures too. This page publishes aggregates only: no card content is reproduced, no card or creator is named, nothing is downloadable. Individual cards belong to their creators; the shape of the ecosystem is fair observation.

How is the crowding index (lift) computed?

lift = a tag's share of all chats ÷ its share of all cards, over the 59 tags with at least 250 cards. A lift of 4.22 means cards wearing that tag average 4.22× the universe-wide chats per card — demand is over-rewarding the tag. We cross-checked with a second recipe (occurrence rate in the top-1,000 ÷ rate overall); amplifiers and red oceans point the same way under both.

Does low lift mean “don't write that kind of card”?

No. Low lift means the lane is thick with supply and average returns are diluted — not that a single card can't break out. The redemption lane holds 1,804 cards and still has million-chat hits. It's a crowding signal, not a quality verdict. And the high-lift lanes (multi-character, simulators) carry real engineering cost — which is exactly why supply lags.

Do these findings transfer to English communities (Chub / JanitorAI)?

Extrapolate with care. This is a single-platform sample of a Chinese, mobile-first, women-audience-dominant ecosystem. English communities differ structurally: chara_card_v2/v3 formats, a dedicated lorebook field, different gender and genre mixes. Please cite these numbers in the “Chinese card ecosystem” frame only.

Why is there no lorebook-attachment rate?

Because this universe has no separate lorebook field — we checked all 1,000 top-card detail payloads and the attachment field is empty on every one. Lore lives in greeting panels, creator notes and hidden prompts instead. That's a different engineering culture from Tavern-style cards (character_book in the v2/v3 spec), and it's exactly where content gets lost when cards migrate across communities.

Can I cite this page?

Yes, freely. Convention: Foreverse Research, “The Character Card Census”, 2026-07, page URL. Keep the snapshot date 2026-07-03 next to any number you republish — the platform moves, and the date is part of the claim. The stat recipes are spelled out in the method section; recomputation under the same recipe is welcome.

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The Character Card Census — Ecosystem Data from 19,776 Chinese Roleplay Cards · Foreverse · Xinmeng