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Push Metadata and Logs to Monte Carlo
monte-carlo-push-ingestion
sickn33/antigravity-awesome-skills
128
An expert agent designed to collect critical data assets—including metadata, data lineage, and query logs—from any data warehouse platform. It uses the push ingestion API to send this data directly to Monte Carlo. This method is essential for integrating data sources that cannot be reliably covered by standard pull collectors, such as custom lineage paths or historical query logs.
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Vector Search and Embedding Similarity Engine
vector-search
ruvnet/ruflo
499
This plugin provides advanced vector search capabilities using two distinct paths. The large-scale path supports millions of vectors via HNSW, ideal for general corpus search. The hot-path router handles small, critical pattern routing (≤11 patterns) with sub-ms latency. Key features include RaBitQ 1-bit quantization for memory efficiency (32× reduction), hyperbolic space search for hierarchical data, and unified cross-namespace search.
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Creating Academic Replication Deposit Packages
aejpol-replication-package
brycewang-stanford/Awesome-Journal-Skills
200
This package assists researchers in assembling a compliant data and code deposit for AEJ: Economic Policy manuscripts. It ensures adherence to the AEA Data and Code Availability Policy by structuring the openICPSR deposit, generating the required README, and managing restricted data access paths. It is critical for passing the mandated pre-publication reproducibility check.
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PPoPP Conference Submission Workflow
ppopp-workflow
brycewang-stanford/Awesome-Journal-Skills
238
A comprehensive guide for planning the entire PPoPP conference submission lifecycle. It outlines the critical path, from initial draft creation, securing machine time, through author rebuttal, artifact evaluation, and final camera-ready submission. Use this to manage the timeline backward from the final conference dates.
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Push Metadata and Logs to Monte Carlo
monte-carlo-push-ingestion
sickn33/agentic-awesome-skills
239
An expert agent designed to collect critical data assets—including metadata, data lineage, and query logs—from any data warehouse platform. It uses the push ingestion API to send this data directly to Monte Carlo. This method is essential for integrating data sources that cannot be reliably covered by standard pull collectors, such as custom lineage paths or historical query logs.
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