Processament de dades

Transformació i anàlisi sintàctica de dades

Skills: 1513–1536 de 13439
mims-harvard

tooluniverse-image-analysis

mims-harvard

Production-ready microscopy image analysis and quantitative imaging data skill for colony morphometry, cell counting, fluorescence quantification, and statistical analysis of imaging-derived measurements. Processes ImageJ/CellProfiler output (area, circularity, intensity, cell counts), performs Dunnett's test, Cohen's d effect size, power analysis, Shapiro-Wilk normality tests, two-way ANOVA, polynomial regression, natural spline regression with confidence intervals, and comparative morphometry. Supports CSV/TSV measurement tables, multi-channel fluorescence data, colony swarming assays, and neuron counting datasets. Use when analyzing microscopy measurement data, colony area/circularity, cell count statistics, swarming assays, co-culture ratio optimization, or answering questions about imaging-derived quantitative data.

Processament de dades 1,8 k fa 8 mesos
mims-harvard

tooluniverse-chemical-compound-retrieval

mims-harvard

Retrieves chemical compound information from PubChem and ChEMBL with disambiguation, cross-referencing, and quality assessment. Creates comprehensive compound profiles with identifiers, properties, bioactivity, and drug information. Use when users need chemical data, drug information, or mention PubChem CID, ChEMBL ID, SMILES, InChI, or compound names.

Processament de dades 1,8 k fa 8 mesos
mims-harvard

tooluniverse-multiomic-disease-characterization

mims-harvard

Comprehensive multi-omics disease characterization integrating genomics, transcriptomics, proteomics, pathway, and therapeutic layers for systems-level understanding. Produces a detailed multi-omics report with quantitative confidence scoring (0-100), cross-layer gene concordance analysis, biomarker candidates, therapeutic opportunities, and mechanistic hypotheses. Uses 80+ ToolUniverse tools across 8 analysis layers. Use when users ask about disease mechanisms, multi-omics analysis, systems biology of disease, biomarker discovery, or therapeutic target identification from a disease perspective.

Processament de dades 1,8 k fa 8 mesos
mims-harvard

tooluniverse-clinical-guidelines

mims-harvard

Search and retrieve clinical practice guidelines across 12+ authoritative sources including NICE, WHO, ADA, AHA/ACC, NCCN, SIGN, CPIC, CMA, CTFPHC, GIN, MAGICapp, PubMed, EuropePMC, TRIP, and OpenAlex. Covers disease management, cardiology, oncology, diabetes, pharmacogenomics, and more. Use when users ask about clinical guidelines, treatment recommendations, standard of care, evidence-based medicine, or drug-gene dosing recommendations.

Processament de dades 1,8 k fa 8 mesos
mims-harvard

setup-tooluniverse

mims-harvard

Install and configure ToolUniverse with MCP integration for any AI coding client (Cursor, Claude Desktop, Windsurf, VS Code, Codex, Gemini CLI, Trae, Cline, Antigravity, OpenCode, etc.). Covers uv/uvx setup, MCP configuration, API key walkthrough, skill installation, and upgrading. Use when setting up ToolUniverse, configuring MCP servers, troubleshooting installation issues, upgrading versions, or when user mentions installing ToolUniverse or setting up scientific tools.

Eines de línia d’ordres 1,8 k fa 8 mesos
mims-harvard

tooluniverse-metabolomics-analysis

mims-harvard

Analyze metabolomics data including metabolite identification, quantification, pathway analysis, and metabolic flux. Processes LC-MS, GC-MS, NMR data from targeted and untargeted experiments. Performs normalization, statistical analysis, pathway enrichment, metabolite-enzyme integration, and biomarker discovery. Use when analyzing metabolomics datasets, identifying differential metabolites, studying metabolic pathways, integrating with transcriptomics/proteomics, discovering metabolic biomarkers, performing flux balance analysis, or characterizing metabolic phenotypes in disease, drug response, or physiological conditions.

Revisió de codi 1,8 k fa 8 mesos
mims-harvard

tooluniverse-immunotherapy-response-prediction

mims-harvard

Predict patient response to immune checkpoint inhibitors (ICIs) using multi-biomarker integration. Given a cancer type, somatic mutations, and optional biomarkers (TMB, PD-L1, MSI status), performs systematic analysis across 11 phases covering TMB classification, neoantigen burden estimation, MSI/MMR assessment, PD-L1 evaluation, immune microenvironment profiling, mutation-based resistance/sensitivity prediction, clinical evidence retrieval, and multi-biomarker score integration. Generates a quantitative ICI Response Score (0-100), response likelihood tier, specific ICI drug recommendations with evidence, resistance risk factors, and a monitoring plan. Use when oncologists ask about immunotherapy eligibility, checkpoint inhibitor selection, or biomarker-guided ICI treatment decisions.

Revisió de codi 1,8 k fa 8 mesos
mims-harvard

tooluniverse-cancer-variant-interpretation

mims-harvard

Provide comprehensive clinical interpretation of somatic mutations in cancer. Given a gene symbol + variant (e.g., EGFR L858R, BRAF V600E) and optional cancer type, performs multi-database analysis covering clinical evidence (CIViC), mutation prevalence (cBioPortal), therapeutic associations (OpenTargets, ChEMBL, FDA), resistance mechanisms, clinical trials, prognostic impact, and pathway context. Generates an evidence-graded markdown report with actionable recommendations for precision oncology. Use when oncologists, molecular tumor boards, or researchers ask about treatment options for specific cancer mutations, resistance mechanisms, or clinical trial matching.

Processament de dades 1,8 k fa 8 mesos
alibaba

higress-wasm-go-plugin

alibaba

Develop Higress WASM plugins using Go 1.24+. Use when creating, modifying, or debugging Higress gateway plugins for HTTP request/response processing, external service calls, Redis integration, or custom gateway logic.

Desenvolupament d’API 9,6 k fa 9 mesos
apify

apify-ecommerce

apify

Scrape e-commerce data for pricing intelligence, customer reviews, and seller discovery across Amazon, Walmart, eBay, IKEA, and 50+ marketplaces. Use when user asks to monitor prices, track competitors, analyze reviews, research products, or find sellers.

Automatització 2,5 k fa 8 mesos
akseolabs-seo

seo-coach

akseolabs-seo

Beginner-first SEO coaching for people who want to learn by doing one safe, verifiable step at a time. Use for SEO 陪跑、學 SEO、逐步檢查網站、看懂 Search Console/GA4、零付費工具的手動無痕 SERP、關鍵字與搜尋意圖、 內容差距、基礎網站架構、content brief、四篇 SEO 寫作實作、流量或排名問題教學, 以及 robots.txt、sitemap、title、canonical、Core Web Vitals 等概念與操作問題。 Do not use for a one-shot full-site audit report or health score, ghostwritten content delivery, PBN/site building, or paid-ad-only advice.

Processament de dades 188 fa 1 mes
davila7

axolotl

davila7

Expert guidance for fine-tuning LLMs with Axolotl - YAML configs, 100+ models, LoRA/QLoRA, DPO/KTO/ORPO/GRPO, multimodal support

Desenvolupament d’API 32,9 k fa 9 mesos
davila7

evaluating-code-models

davila7

Evaluates code generation models across HumanEval, MBPP, MultiPL-E, and 15+ benchmarks with pass@k metrics. Use when benchmarking code models, comparing coding abilities, testing multi-language support, or measuring code generation quality. Industry standard from BigCode Project used by HuggingFace leaderboards.

Eines de línia d’ordres 32,9 k fa 9 mesos
davila7

llamaindex

davila7

Data framework for building LLM applications with RAG. Specializes in document ingestion (300+ connectors), indexing, and querying. Features vector indices, query engines, agents, and multi-modal support. Use for document Q&A, chatbots, knowledge retrieval, or building RAG pipelines. Best for data-centric LLM applications.

Processament de dades 32,9 k fa 9 mesos
davila7

ray-data

davila7

Scalable data processing for ML workloads. Streaming execution across CPU/GPU, supports Parquet/CSV/JSON/images. Integrates with Ray Train, PyTorch, TensorFlow. Scales from single machine to 100s of nodes. Use for batch inference, data preprocessing, multi-modal data loading, or distributed ETL pipelines.

Automatització 32,9 k fa 9 mesos
davila7

deepspeed

davila7

Expert guidance for distributed training with DeepSpeed - ZeRO optimization stages, pipeline parallelism, FP16/BF16/FP8, 1-bit Adam, sparse attention

Processament de dades 32,9 k fa 9 mesos
davila7

model-pruning

davila7

Reduce LLM size and accelerate inference using pruning techniques like Wanda and SparseGPT. Use when compressing models without retraining, achieving 50% sparsity with minimal accuracy loss, or enabling faster inference on hardware accelerators. Covers unstructured pruning, structured pruning, N:M sparsity, magnitude pruning, and one-shot methods.

Processament de dades 32,9 k fa 9 mesos
davila7

moe-training

davila7

Train Mixture of Experts (MoE) models using DeepSpeed or HuggingFace. Use when training large-scale models with limited compute (5× cost reduction vs dense models), implementing sparse architectures like Mixtral 8x7B or DeepSeek-V3, or scaling model capacity without proportional compute increase. Covers MoE architectures, routing mechanisms, load balancing, expert parallelism, and inference optimization.

Automatització 32,9 k fa 9 mesos
davila7

evaluating-llms-harness

davila7

Evaluates LLMs across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). Use when benchmarking model quality, comparing models, reporting academic results, or tracking training progress. Industry standard used by EleutherAI, HuggingFace, and major labs. Supports HuggingFace, vLLM, APIs.

Eines de línia d’ordres 32,9 k fa 9 mesos
Mathews-Tom

immune

Mathews-Tom

'Hybrid adaptive memory: Cheatsheet (positive patterns pre-generation) and Immune (negative patterns post-generation) with Hot/Cold tiered auto-learning. Triggers on: "scan for errors", "immune scan", "check output quality", "antibody scan". NOT for PR review (use pr-review) or repo audits (use repo-sentinel).'

Revisió de codi 337 fa 6 mesos
Mathews-Tom

prompt-lab

Mathews-Tom

'LLM prompt engineering: analyzes failure modes, generates variants (direct, few-shot, CoT), designs rubrics, produces test suites. Triggers on: "prompt engineering", "generate prompt variants", "A/B test prompts", "optimize prompt", "improve this prompt". NOT for SKILL.md files, use skill-evaluator.'

Processament de dades 337 fa 6 mesos
Mathews-Tom

manuscript-provenance

Mathews-Tom

'Computational provenance audit verifying every number, table, and figure in a manuscript derives from code, not manual entry. Triggers on: "check provenance", "verify reproducibility", "audit my pipeline", "are my numbers from code", "provenance audit". Companion to manuscript-review (prose audit).'

Processament de dades 337 fa 5 mesos
fcakyon

mongodb-usage

fcakyon

This skill should be used when user asks to "query MongoDB", "show database collections", "get collection schema", "list MongoDB databases", "search records in MongoDB", or "check database indexes".

Processament de dades 1,2 k fa 10 mesos
EveryInc

agent-browser

EveryInc

Browser automation using Vercel's agent-browser CLI. Use when you need to interact with web pages, fill forms, take screenshots, or scrape data. Alternative to Playwright MCP - uses Bash commands with ref-based element selection. Triggers on "browse website", "fill form", "click button", "take screenshot", "scrape page", "web automation".

Agents 25,7 k fa 9 mesos