Plugins

2 plugins

@brycewang-stanford

Twelve-skill bundle covering the Cell manuscript lifecycle: workflow router, scope/significance fit, single-narrative framing, the Highlights + eTOC + Graphical Abstract trio, the ≤150-word Summary, main-text writing, display items, STAR Methods + Key Resources Table, data/code availability, Cell Press author–date references, submission preflight + cover letter, and reviewer rebuttal.

9 skills · plugin

@brycewang-stanford

50 Brycewang Aer Skills

Nine-skill stack for top-5 economics manuscripts (AER / AER: Insights / AEJ): topic selection, modern causal identification (DiD / IV / RDD / SCM / Bartik), referee-anticipating robustness, Keith-Head-style introductions, AER booktabs tables, AEA Data and Code Availability deposits (openICPSR-ready), submission preflight, and R&R rebuttal letters. Ships Stata / R / Python templates and classic-AER

7 skills · plugin

Results for “data-table”

4 skills

flow-data-tables

Configure the Data Table screen component in Salesforce Screen Flows for row selection, including single/multi-select, column setup, and downstream consumption of selected rows.

More results

kol-creator-discovery

Use this skill when a user needs KOL or influencer research, creator email lookup, similar-creator discovery, outreach-list building, influencer prospecting, or a contact table from TikTok, Instagram, or YouTube profile URLs. It uses AIsa's WaveInflu APIs to find verified creator emails, match similar YouTube or TikTok creators, enrich each recommended profile with contact emails, and return an outreach-ready Markdown table without inventing missing data. Use when: the user needs YouTube search, trend discovery, channel research, or SERP analysis.

Answer any data question, scaling effort from a one-number lookup to a full stakeholder-ready analysis with a recommendation.

alterlab-datamol

Wraps RDKit in a high-level, pandas-friendly datamol interface with sensible defaults for everyday drug discovery — SMILES/SDF loading into DataFrames, molecule standardization, descriptors, fingerprints, Butina clustering, 3D conformer generation, scaffold analysis, and parallel batch processing, returning native rdkit.Chem.Mol objects. Use when running standard cheminformatics pipelines on molecule tables with minimal boilerplate; for low-level control, custom sanitization, or specialized algorithms prefer alterlab-rdkit. Part of the AlterLab Academic Skills suite.