a

a partial markdown implementation with angular.js

Hacker News

a partial markdown implementation with angular.js

Because this just uses angular.js templates, the HTML is sanitized, and only the DOM nodes that represent data that's changed are manipulated while editing the markdown source. This is also an example of how partial templates have access to variables and how the variables can be set with ng-init before including the template with ng-include.

Share card

Actual performance

4points
1comments
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Strong signals: including · Missing: supports, reddit linkedin, podcasting
56%56% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos
52%52% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io, including · Missing: https docs, excited, just released
48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
28%28% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
20%20% predicted probability of success on BetaList, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

St
Stellar.js53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Stellar.js

Hacker News3
Ta
Tasskr remade with backbone.js47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Tasskr remade with backbone.js

Hacker News2
sm
smooth_operator.js53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

smooth_operator.js

Hacker News2
es
escalate.js59%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

escalate.js

Hacker News1
Un
Underscore.js for Objective-C39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Underscore.js for Objective-C

Hacker News120
Se
Selector.js53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Selector.js

Hacker News2
Bi
BigVideo.js53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

BigVideo.js

Hacker News244
st
string.js48%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

string.js

Hacker News3
st
streamplayer.js67%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

streamplayer.js

Hacker News3
Da
Datalog.js53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Datalog.js

Hacker News3