Plugins

9 plugins

Azure API Center Management

For Azure developers managing API Center resources with Python and .NET SDKs.

4 skills · plugin

Analyze Single-Cell RNA-Seq

Analyze single-cell RNA-seq data using Scanpy, including quality control, normalization, clustering, marker gene identification, and visualization.

9 skills · plugin

@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

ISO 27001 Audit Pipeline

Pressure-test an ISMS and generate audit evidence for ISO 27001 certification readiness.

9 skills · plugin

@matteobortolazzo

cenci workflow layer: portable engineering conventions and Claude Code's gated GitHub ticket-to-PR pipeline

27 skills · plugin

Robotik-Recht Deutschland/EU: Maschinenverordnung, KI-VO, Produkthaftung, ProdSG, Datenschutz, CRA, Data Act, CE, Marktüberwachung, Unfälle, Rückruf, Verträge und Robotik-Testakte.

2 skills · plugin

@brycewang-stanford

Twelve HRI-specific skills for the ACM/IEEE International Conference on Human-Robot Interaction and its interdisciplinary, human-subjects-centered evidence culture, grounded in the HRI 2026/2027 calls, humanrobotinteraction.org, the ACM Digital Library, IEEE Xplore, and dblp.

2 skills · plugin

@brycewang-stanford

Twelve DAC-specific skills for the ACM/IEEE Design Automation Conference (the Chips to Systems Conference) and its double-blind Research Manuscript track, grounded in the DAC 2026 (63rd) call, dac.com, IEEE CEDA, ACM SIGDA, the ACM Digital Library, and dblp.

2 skills · plugin

@alirezarezvani

C Level Advisor

33 C-level advisory skills + c-level-agents plugin layer: virtual board of directors (CEO, CTO, COO, CPO, CMO, CFO, CRO, CISO, CHRO) plus General Counsel, CDO, CAIO, CCO, and VP of Engineering (DORA delivery throughput analyzer, engineering hiring funnel calculator with conversion + pipeline gap, eng team structure designer with squad/tribe + manager-trigger), executive mentor, founder coach, orch

27 skills · plugin

Results for “ce”

30 skills

Cellxgene Census

Query the CZ CELLxGENE Census programmatically for versioned public single-cell and spatial transcriptomics data, enabling efficient access to cell metadata, gene expression slices, summary counts, and embeddings without downloading whole datasets.

30.2k · bundle

Analyzing Certificate Transparency For Phishing

Monitor Certificate Transparency logs using crt.sh and Certstream to detect phishing domains, lookalike certificates, and unauthorized certificate issuance targeting your organization.

24.6k · bundle

Universal Single Cell Annotator

Annotates single-cell RNA-seq data by scoring marker genes, transferring labels with CellTypist, or reasoning over cluster markers with an LLM.

Annotates single-cell RNA-seq data by scoring marker genes, transferring labels with CellTypist, or reasoning over marker lists with an LLM.

Runs standard single-cell RNA-seq analysis with Scanpy, covering QC, normalization, dimensionality reduction, clustering, marker identification, visualization, and conversion of R single-cell formats to h5ad.

Analyze RNA velocity in single-cell RNA-seq data with scVelo, estimating cell state transitions from unspliced/spliced mRNA dynamics, inferring trajectory directions, computing latent time, and identifying driver genes.

More results

Analyze single-cell RNA-seq data using Scanpy, including quality control, normalization, clustering, marker gene identification, and visualization.

Analyze single-cell RNA-seq data with Scanpy, covering quality control, normalization, dimensionality reduction, clustering, marker gene identification, and visualization.

Analyze single-cell RNA-seq data with Scanpy, covering quality control, normalization, clustering, marker gene identification, visualization, and trajectory analysis.

Run standard single-cell RNA-seq analysis pipelines: QC, normalization, dimensionality reduction, clustering, differential expression, and visualization using Scanpy.

30.2k · bundle

Manages annotated data matrices for single-cell genomics, covering creation, I/O, concatenation, and manipulation of AnnData objects in h5ad and zarr formats.

nimoqup046-collab

Analyze single-cell RNA-seq data with Scanpy, covering quality control, normalization, clustering, marker gene identification, visualization, and trajectory analysis.

lucaspmarie-a11y

Analyze single-cell RNA-seq data with Scanpy, covering quality control, normalization, clustering, marker gene identification, visualization, and trajectory analysis.

Create, read, manipulate, and store annotated data matrices using the AnnData Python package, designed for single-cell genomics and general-purpose annotated data workflows.

30.2k · bundle

Analyzes uploaded data files with full Python access, producing cleaned datasets, statistical reports, charts, and dashboards via the CellCog coding agent.

Create, manipulate, and analyze complex networks and graphs using the NetworkX Python package.

Infer gene regulatory networks from gene expression data using scalable algorithms (GRNBoost2, GENIE3) with support for distributed computation.

30.2k · bundle

Create, analyze, and visualize complex networks and graphs in Python using NetworkX, including graph construction, algorithms, generators, I/O, and plotting.

johnalbertini14-glitch

Tracks crypto prices, wallet balances, portfolio values, and CEX history via a command-line interface, with support for Polymarket prediction markets.

schattenspiegel

Create, review, debug, test, or reproduce Python Jupyter notebooks by inspecting format, executing cells top-to-bottom in a clean kernel, and verifying outputs.

Trains machine learning models on genomic interval data from BED files, including region embeddings, single-cell ATAC-seq analysis, and consensus peak building.

Cx Abandonment Analysis

Analyzes chat and call abandonment, queue patience, and what a high FCR may be hiding when abandoned contacts never become tickets.

Train unsupervised machine learning models on genomic interval data from BED files, including region embeddings, single-cell ATAC-seq analysis, and consensus peak building.

30.2k · bundle

Create, analyze, and visualize complex networks and graphs in Python with NetworkX, including graph algorithms, community detection, synthetic network generation, and multiple I/O formats.

30.2k · bundle

Manage biological datasets and models with LaminDB, an open-source lineage-native lakehouse. Covers setup, artifact registration, query/search, lineage tracking, validation, ontology-backed annotation, collections, branches, storage, and workflow integrations.

30.2k · bundle

Economic Calendar Fetcher

Fetch upcoming economic events and data releases using the FMP API, including central bank decisions, employment reports, inflation data, GDP releases, and other market-moving indicators for specified date ranges.

Query the Cancer Dependency Map (DepMap) for cancer cell line gene dependency scores, drug sensitivity data, and gene effect profiles to identify cancer-specific vulnerabilities, synthetic lethal interactions, and validate oncology drug targets.

30.2k · bundle

Query the Cancer Dependency Map (DepMap) for cancer cell line gene dependency scores (CRISPR Chronos), drug sensitivity data, and gene effect profiles. Use for identifying cancer-specific vulnerabilities, synthetic lethal interactions, and validating oncology drug targets.

Hunting For Cobalt Strike Beacons

Detect Cobalt Strike beacon network activity using TLS certificate signatures, JA3/JA3S/JARM fingerprints, HTTP C2 profile matching, beacon jitter analysis, and named pipe detection via Zeek, Suricata, and Python PCAP analysis.

24.6k · bundle

High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.

30.2k · bundle