External SSL VPN / remote-access appliance attack matrix — Cisco ASA/AnyConnect, Fortinet FortiGate/FortiOS, Citrix NetScaler/ADC, Palo Alto GlobalProtect, Pulse Secure / Ivanti Connect Secure, SonicWall, F5 Big-IP. Covers version fingerprinting, CVE matrix (2018-2026), AAA backend identification, default credentials, configuration-disclosure paths, pre-auth RCE/SSRF/path-traversal exploits where applicable. Built from authorized-engagement Cisco ASA testing plus 2024-2026 enterprise VPN CVE landscape. Use whenever the target's perimeter exposes any SSL VPN appliance or remote-access gateway — these are the most common initial-access points in 2024-2026 actor TTPs.
日本語の概要は準備中です。原文の説明を表示しています。
elementalsouls/Claude-BugHunter☆ 5,0722026年10月12日 更新
Competitor research and intelligence skill. Takes a user's company (with optional seed competitor URLs), auto-discovers additional competitors via Browserbase Search API, deeply researches each using a 4-lane pattern (marketing surface, external signal, public benchmarks, strategic diff vs the user's company), and compiles the results into an HTML report with four views: overview, per-competitor deep dive, side-by-side feature/pricing matrix, and a chronological mentions feed (news, reviews, social, comparison pages, and public benchmarks). Use when the user wants to: (1) analyze competitors, (2) build a competitive matrix, (3) extract competitor pricing / features, (4) find comparison pages and online mentions of competitors, (5) surface public benchmarks. Triggers: "competitor analysis", "analyze competitors", "competitive intel", "competitor research", "competitor pricing", "feature comparison", "price comparison", "find comparisons", "who's comparing us", "competitor mentions", "competitor benchmarks".
日本語の概要は準備中です。原文の説明を表示しています。
browserbase/skills☆ 3,7312026年9月30日 更新
[omh] Evaluating a plugin, connector, or API for adoption: external connector readiness - assess whether a named plugin, connector, API, data provider, or multimodal route is safe, affordable, fresh, and observable; use executor-runtime-readiness for coding-owner choice and toolbelt-readiness for missing capability inventory. Use when the user says: external-connector-readiness, external connector readiness, connector readiness matrix, plugin readiness matrix, provider readiness, api readiness, connector adoption, external plugin adoption.
日本語の概要は準備中です。原文の説明を表示しています。
rlaope/oh-my-hermes☆ 3,3572026年10月13日 更新
A cyber-slick, dark-only Matrix-inspired interface defined by minimalist fashion, high-tech digital elements
日本語の概要は準備中です。原文の説明を表示しています。
bergside/awesome-design-skills☆ 3,1492026年6月28日 更新
Matrix/Element messaging channel for Clawdbot agent
日本語の概要は準備中です。原文の説明を表示しています。
SharpAI/DeepCamera☆ 3,0942026年9月17日 更新
Use when building a binary classification model from an expression matrix or other omics feature matrix with LASSO logistic regression, cross-validation, and coefficient path visualization. NOT for: multiclass classification, survival/Cox models, or ordinary linear regression.
日本語の概要は準備中です。原文の説明を表示しています。
aipoch/medical-research-skills☆ 1,9482026年9月17日 更新
Use when estimating relative immune cell infiltration from a bulk expression matrix with a CIBERSORT-style nu-SVR deconvolution workflow based on an LM22 signature matrix, comparing one case group against one control group, and generating structured tables plus immune-fraction plots. NOT for single-cell RNA-seq, spatial data, clinical diagnosis, or workflows that require the original hosted CIBERSORT web service.
日本語の概要は準備中です。原文の説明を表示しています。
aipoch/medical-research-skills☆ 1,9482026年9月17日 更新
Für Beziehungsmatrix Personen/Taten: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.
日本語の概要は準備中です。原文の説明を表示しています。
Klotzkette/claude-fuer-deutsches-recht☆ 1,7002026年10月11日 更新
Build, refresh, report, or probe an accessibility coverage matrix across criteria, surfaces, and evidence methods. Use when assessing coverage with the accessibility runtime harness and generated evidence bundle.
日本語の概要は準備中です。原文の説明を表示しています。
microsoft/hve-core☆ 1,5212026年10月13日 更新
Use this skill when producing a polished, Commonly-branded deliverable (.docx brief / memo, .xlsx data matrix, .pptx deck) and you do not have specific brand guidance from the user. Trigger on: 'write me a brief', 'one-pager', 'memo', 'data sheet', 'status matrix', 'short deck', 'summary deck', 'closing slide', 'final deliverable'. Routes to `officecli merge` with one of three pre-built starter templates that already carry the Commonly palette, fonts, and structure — so you populate content with one merge call instead of 30 individual `officecli set` commands. DO NOT use for fundraising decks (use `officecli-pitch-deck`), academic papers (use `officecli-academic-paper`), or financial models (use `officecli-financial-model`).
日本語の概要は準備中です。原文の説明を表示しています。
Team-Commonly/commonly☆ 1,3612026年10月10日 更新
Compare two or more companies, products, or platforms across pricing, features, positioning, and docs. Use this skill whenever the user says "compare X vs Y", "how does X stack up against Y", "alternatives to X", "competitive landscape of …", "X vs Y vs Z", or asks for a competitor matrix. Uses search to discover competitors when the user only names a category, then scrape for each competitor's homepage, pricing page, and features/docs. Returns a normalized comparison matrix as JSON.
日本語の概要は準備中です。原文の説明を表示しています。
firecrawl/web-agent☆ 1,2462026年4月20日 更新
Quality control for IMC/MIBI data across pixel, channel, image, slide, and batch levels, covering Poisson-count SNR (cell-level Gaussian-mixture and empty-channel comparison), spillover-matrix QC (the three physical sources), drift and the missing EQ-bead analog, acquisition artifacts, and sample-of-origin batch effects. Use when deciding whether to keep or drop a channel, ROI, or slide, distinguishing a dim antibody from a failed one, reading a spillover matrix, or diagnosing batch-driven clustering before analysis.
日本語の概要は準備中です。原文の説明を表示しています。
GPTomics/bioSkills☆ 1,2192026年8月15日 更新
Balances Hi-C contact matrices (ICE via cooler.balance_cooler, KR/SCALE/VC context), computes distance-decay expected with cooltools (expected_cis per-diagonal P(s), expected_trans scalar), builds observed/expected (O/E) matrices, and diagnoses polymer state from the P(s) log-derivative. Covers the within-matrix-vs-cross-sample distinction (balancing is NOT a normalizer), the equal-visibility assumption that CNV/aneuploidy violates (use raw counts for copy-number), cis-only balancing, mad_max/blacklist masking before balancing, multiplicative cooler weights vs divisive juicer weights, and the resolution-vs-depth budget. Use when balancing a .cool/.mcool, computing expected or P(s), making O/E matrices for compartments/loops, deciding ICE vs KR vs SCALE, choosing a resolution for a given depth, or troubleshooting NaN/all-NaN balanced matrices; route cross-sample comparison to hic-differential.
日本語の概要は準備中です。原文の説明を表示しています。
GPTomics/bioSkills☆ 1,2192026年8月15日 更新
Corrects fluorophore spillover (conventional compensation) or spectral overlap (spectral unmixing) and applies variance-stabilizing transforms (logicle/biexponential, arcsinh, log) for flow and mass cytometry. Covers spillover-matrix estimation from single-stain controls, AutoSpill, the spillover spreading matrix and why panel design (not compensation) bounds resolution, compensate-then-transform ordering, and arcsinh cofactor choice (5 for CyTOF, ~150 for fluorescence, per-channel via flowVS). Use when correcting spectral overlap, preparing data for gating/clustering, choosing logicle vs arcsinh, deciding a cofactor, or distinguishing compensation from spectral unmixing.
日本語の概要は準備中です。原文の説明を表示しています。
GPTomics/bioSkills☆ 1,2192026年8月15日 更新
Imports gene expression count matrices from featureCounts, HTSeq, STAR ReadsPerGene, Salmon/kallisto via tximport or tximeta, RSEM, 10X Genomics MTX/H5, AnnData H5AD, and RDS. Handles silent-miscounting traps (featureCounts -p v2.0.2 API break, STAR strandedness column choice, salmon NumReads-sum without tximport, RSEM non-integer expected_count, GENCODE _PAR_Y suffix, zero-length-transcript TPM divide-by-zero), and encodes the tximport countsFromAbundance decision tree with the "lengthScaledTPM is not TPM" warning. Use when assembling a gene-by-sample count matrix from aligner or quantifier output, importing salmon/kallisto for DESeq2 vs limma-voom, choosing strandedness column for STAR, debugging zero-count panics, or building tx2gene mapping.
日本語の概要は準備中です。原文の説明を表示しています。
GPTomics/bioSkills☆ 1,2192026年8月15日 更新
Aligns sample metadata with count matrices and constructs design matrices for downstream DE, handling the alphabetical-reference-level trap (relevel BEFORE DESeq), LRT reduced-model rules, the interaction-term resultsNames trap, continuous-covariate scaling and splines, repeated measures via duplicateCorrelation or dream, high-cardinality categorical pseudo-singular designs, sample swap detection via XIST/RPS4Y1 expression and somalier/NGSCheckMate genotypes, SABV (sex-as-biological-variable) mandate, Simpson's-paradox collapsing of technical replicates, and the `~ 0 + group` parameterization for clean contrasts. Use when building a design matrix, troubleshooting reversed fold-change direction, encoding paired or repeated-measures designs, detecting sample swaps, deciding sex-as-covariate, or aggregating technical replicates.
日本語の概要は準備中です。原文の説明を表示しています。
GPTomics/bioSkills☆ 1,2192026年8月15日 更新
Analyzes pooled CRISPR screens with MAGeCK (Li et al 2014), covering count generation (mageck count), the RRA two-condition workflow (mageck test using alpha-RRA over per-sgRNA negative-binomial p-values), the MLE multi-condition workflow (mageck mle with explicit design matrix and beta-score output), normalization choice (median vs total vs control-sgRNA vs spike-in), sgRNA efficiency injection, paired-sample testing, time-course design, drug-screen versus dropout-screen design matrices, MAGeCKFlute and MAGeCK-VISPR downstream visualization, and decision logic for when to use MAGeCK vs JACKS / BAGEL2 / drugZ / Chronos. Use when running a fresh CRISPR screen analysis, picking RRA vs MLE for the experimental design, choosing a normalization method from QC signatures, debugging MLE convergence failure or NaN beta scores, comparing MAGeCK output across tools, or building a batch-aware multi-cell-line / multi-condition MLE design matrix.
日本語の概要は準備中です。原文の説明を表示しています。
GPTomics/bioSkills☆ 1,2192026年8月15日 更新
Handles batch effects in bulk RNA-seq via design-matrix inclusion (the correct path for DE), ComBat/ComBat-seq for visualization, SVA for unknown latent factors, RUVSeq for negative-control-gene-anchored unwanted variation, and limma::removeBatchEffect for plotting only. Encodes the Nygaard 2016 cardinal sin against testing on a batch-corrected matrix, the choice between SVA/RUVg/RUVs/RUVr, the confounding non-identifiability problem, the single-cell boundary (Harmony/MNN are NOT for bulk), and the Goh 2017 harmonization critique. Use when designing a DE analysis with batch structure, troubleshooting batch-dominated PCA, choosing ComBat vs ComBat-seq, handling unknown batch via SVA, integrating across studies, or deciding when (rarely) to subtract batch.
日本語の概要は準備中です。原文の説明を表示しています。
GPTomics/bioSkills☆ 1,2192026年8月15日 更新
Generate correct MATLAB code using the Symbolic Math Toolbox. Use when the user asks for symbolic computations, analytical solutions, symbolic differentiation/integration, equation solving, or converting symbolic results to numeric MATLAB functions. Also use when converting differential equations to transfer functions or state-space form, extracting PDE coefficients (pdeCoefficients), symbolic-to-C code generation (matlabFunction + codegen), symbolic matrix variables (symmatrix), physical units and constants (symunit, newUnit), or rewriting/combining algebraic expressions (rewrite, combine).
日本語の概要は準備中です。原文の説明を表示しています。
matlab/matlab-agentic-toolkit☆ 1,1572026年10月9日 更新
Exchange data between Excel and MATLAB using Spreadsheet Link VBA macros and worksheet functions. Use when writing Excel VBA macros that call MLPutMatrix, MLGetMatrix, MLPutVar, MLGetVar, MLPutRanges, MLEvalString, MLGetFigure, or MatlabRequest.
日本語の概要は準備中です。原文の説明を表示しています。
matlab/matlab-agentic-toolkit☆ 1,1572026年10月9日 更新
Structured legal risk assessment with 5x5 Severity x Likelihood matrix. Use for risk scoring, risk registers, escalation decisions, and risk memos.
日本語の概要は準備中です。原文の説明を表示しています。
borghei/Claude-Skills☆ 9012026年10月7日 更新
Extract structured data from multiple documents into comparison matrix with citations. Use for bulk document review.
日本語の概要は準備中です。原文の説明を表示しています。
borghei/Claude-Skills☆ 9012026年10月7日 更新
Run cohort analysis: retention matrix and LTV by cohort. Churn scoring → churn-risk. "build a retention matrix"
日本語の概要は準備中です。原文の説明を表示しています。
indranilbanerjee/digital-marketing-pro☆ 8772026年10月12日 更新
Guide to analyze multiple documents (PDF, DOCX) against user-defined columns and produce a structured Excel output with citations. Use when the user wants to: (1) Extract specific information from multiple documents into a table, (2) Compare clauses or provisions across contracts, (3) Create a document review matrix with source citations. Triggers on: 'tabular review', 'document matrix', 'extract from documents', 'compare across documents', 'review multiple contracts'.
日本語の概要は準備中です。原文の説明を表示しています。
lawve-ai/awesome-legal-skills☆ 8632026年10月3日 更新