Skill comparison

Compare agent skills before installing.

Put high-signal skills side by side and inspect quality, adoption, freshness, install readiness, use-case fit, and warnings in one place.

Comparing 1 skill

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Decision summary

Stock Feature Engineering is the strongest overall pick here because it has a 30/100 readiness score and fits Finance and quant.

Strongest overall

Stock Feature Engineering

Do a manual repository review before adding this to an agent workflow.

Fastest prototype

Stock Feature Engineering

Best first install candidate based on install readiness and adoption.

Freshest repo

Stock Feature Engineering

Most recent maintenance signal among this shortlist.

SignalStock Feature Engineering

Created a continuous, homogeneous, and structured 10 GB dataset from self obtained collections of unstructured intraday financial data. Generated features from indicators, statistics, and recent factors. Used multi-disciplined analysis to find feature importance. Attached labels of trends and stop/hold positions for machine learning. Used machine learning to significant features.

Quality
40/100
Needs review
Decision verdict
30/100
Needs manual review

Do a manual repository review before adding this to an agent workflow.

Adoption76 stars
0 installs
FreshnessMay 23, 2020
Use-case fit
Workflow fit
Platform hintsJupyter Notebook, Financial Data, Claude Code
WarningsRepository looks stale · No OpenAgentSkill engagement data yet
Best forFinance and quant workflows · Claude Code teams · builders willing to evaluate younger projects
Not ideal forteams that require actively maintained dependencies · production agents without a repository review
OpenAgentSkill engagement0 views
0 install copies
Install
$ npx skills add hjeffreywang/Stock_feature_engineering