Build the mental modelA cell is a UTXO + data container, not an account balance update.
2
Break down the cell`capacity` is resource, `lock` is permission, `type` is rules, `data` is state.
3
Break down the scriptA script has `code_hash`, `hash_type`, and `args`, linking code and parameters.
4
Separate lock and typelock decides who can spend; type decides whether state transitions are valid.
5
Map it to a transactionSpend old cells as inputs, create new cells as outputs; spent cells become dead cells.
Representative Answer
CKB cell = UTXO + data container
cell = {
capacity, // CKB resource
lock, // who can spend
type?, // optional state rules
data // app state
}
script = { code_hash, hash_type, args }
lock answers: who can spend this cell?
type answers: is the state transition valid?
Why 5/5
Beyond definitionsIt turns the Cell Model into code structure and transaction reasoning.
Clear boundariesIt separates lock and type responsibilities without blurring them.
Transaction modelOld cells are consumed as inputs; new cells are created as outputs.
High demo valueIt shows Nervos Brain can explain CKB internals to developers.
NBNervos Brain · 5/5 Quality Answer
CASE 02 / COMMUNITY KNOWLEDGE / Talk Retrieval
Nervos Talk Discussion Map: Bounded Summary
5 / 5Community Rating
Original Question
“Classify all community discussion posts into several categories and summarize them in detail.”
Detect exhaustive wordingThe user asks for “all posts”; the answer does not pretend full coverage.
2
State the retrieval scopeIt limits the summary to retrieved Talk/community samples.
3
Ground in evidenceIt uses 10 Talk evidence items instead of summarizing from memory.
4
Group into 6 categoriesWeekly updates, governance, protocols, projects, events, tools/apps.
5
Keep the boundary visibleIt gives representative examples while avoiding exhaustive claims.
Representative Answer
This classification only covers the Nervos Talk / community posts and weekly samples retrieved in this run. It should not be treated as an exhaustive map of all posts.
Based on 10 evidence items, the discussions can be grouped into:
1. Ecosystem weekly updates
2. DAO / governance discussions
3. Technical protocol discussions
4. Project and ecosystem updates
5. Community events
6. Tools, wallets and developer experience
The category map is the answer
Weekly Updates
DAO / Governance
Protocols
Project Updates
Community Events
Tools & Apps
NBNervos Brain · 5/5 Quality Answer
CASE 03 / PRODUCT JUDGMENT / Direct Answer
Prediction Market Review: From Idea to Risk to Fix
5 / 5Community Rating
Original Question
“Review a swipe-based prediction market idea using Fiber for small, frequent payments.”
Acknowledge the upsideSwipe interaction lowers friction and supports frequent lightweight participation.
2
Connect Fiber to the use caseSmall repeated payments can fit low-stake, high-frequency prediction flows.
3
Name the core riskThe real question is not “is it fun?” but “does it become a gambling app?”
4
Break down risk sourcesCompliance, payment controls, content quality, liquidity and addictive behavior.
5
Propose a safer directionMove from betting toward light prediction, opinion voting, badges and limits.
Representative Answer
The idea has strengths, but the core risk is not “is it fun?” It is “does this become a gambling app?”
Upside: swipe yes / no lowers decision friction; Fiber small repeated payments fit the usage pattern.
Risk: it can slide from prediction market to gambling, and small repeated payments can amplify addictive behavior.
Fix: shift toward light prediction, opinion voting, badges, limits and cooldowns.