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microelectronics-materials-…/references/ai-skills.md
skillfactor-pipeline 0305dd6362 feat: microelectronics-materials-engineer skill package v0.1.0
2026-08-14 16:59:58 +02:00

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External AI agent skills — microelectronics-materials-engineer

Proven, publicly available AI agent skills mapped to this occupation. Nothing is copied from the sources: every entry is a name, a one-line summary and a link to the upstream skill package. Each section names its source repository, commit, license and retrieval date.

Tiers: core = the skill directly exercises a top market hard skill, tool or method (from gated job-ad evidence) or an essential ESCO competence of this occupation; adjacent = plausibly useful, secondary. Entries are capped at 12 per source and 80 in total per occupation (core first, strongest matches survive); everything beyond the caps is excluded and logged in the pipeline audit trail, not in this package.

Matched deterministically (ISCO group + title/competence keywords, tiered against market evidence + ESCO essentials) by pipeline/p5_enrich_ai_skills.py on 2026-07-14.

Source: anthropics/skills

  • Repository: https://github.com/anthropics/skills (commit f6656c1, retrieved 2026-07-14)
  • License: Apache-2.0; the document skills (docx/pdf/pptx/xlsx) are source-available — see the LICENSE.txt in the upstream skill folder
Skill Tier What it adds Upstream
docx adjacent Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files) or Word templates (.dotx files). Triggers include: any mention of 'Word doc', 'word document', '.docx', '.dotx', or requests to … source
pdf adjacent Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating … source

Source: a5c-ai/babysitter

Skill Tier What it adds Upstream
A/B Test Design core Statistical experiment design and analysis capabilities for product experimentation source
A/B Test Statistical Analyzer core Performs statistical analysis for A/B testing experiments source
statistical-testing core Apply statistical hypothesis testing, significance analysis, A/B test evaluation, and distribution comparisons for data science workflows. source
doe-designer core Design of Experiments planning and analysis skill for factorial and response surface experiments. source
quantitative-methods core Design and execute statistical analyses including regression modeling, hypothesis testing, power analysis, and robustness checks using R, Stata, SPSS, or Python source
simulation-experiment-designer core Simulation experimental design skill for efficient scenario analysis and optimization. source
thought-experiment-design core Construct, analyze, and evaluate philosophical thought experiments to test intuitions, reveal conceptual commitments, and probe theoretical implications source
failure-analysis core Systematic failure analysis methodology for mechanical component failures source
iso14971-risk-analyzer core Comprehensive risk management skill implementing ISO 14971:2019 methodology for medical device risk analysis source
pandas-dataframe-analyzer core Automated DataFrame analysis skill for statistical summaries, missing value detection, data type inference, and memory optimization recommendations. source

Source: AgriciDaniel/claude-ads

Skill Tier What it adds Upstream
ads-test core Design and evaluate paid-ad experiments with hypotheses, randomization units, sample-size and duration assumptions, guardrails, platform experiment tools, analysis, and decision rules. Use for A/B test, split test, experiment design, … source

Source: AgriciDaniel/claude-blog

Skill Tier What it adds Upstream
blog-strategy core Blog strategy development including topic cluster architecture with hub-and-spoke design, audience mapping, competitive landscape analysis, AI citation surface strategy across ChatGPT/Perplexity/AI Overviews, distribution channel planning … source

Source: basicmachines-co/basic-memory

Skill Tier What it adds Upstream
memory-literary-analysis core Analyze a complete literary work into a structured Basic Memory knowledge graph. Covers schema design, entity seeding, chapter-by-chapter processing, cross-referencing, validation, and visualization. source

Source: brycewang-stanford/Auto-Empirical-Research-Skills

Skill Tier What it adds Upstream
c1 core VS-Enhanced Quantitative Design Consultant with Materials & Sampling Enhanced VS 3-Phase process: Avoids obvious experimental designs, proposes context-optimal quantitative strategies Absorbed C4 (Experimental Materials Developer) and D1 … source
law-skills core 9 legal research skills. Trigger: legal research, case law analysis, regulatory compliance. Design: legal databases, citation networks, and judicial analytics tools. source
psychology-research-guide core Psychological research methods, experimental design, and analysis source
statistics-skills core 10 statistical analysis skills. Trigger: statistical tests, Bayesian analysis, hypothesis testing, sampling. Design: method guides covering assumptions, code, and result interpretation. source
academic-baseline core Use when working on any empirical academic research context — paper writing, data analysis, literature review, or any task involving citations, results, or publication artifacts. Establishes non-negotiable principles that govern all other … source
aer-statspai core Use when aer-identification has fixed the design, after methodology choice and before aer-robustness or aer-tables-figures, to run an AER-track analysis with StatsPAI — the agent-native Python engine and MCP server for causal inference, … source
results-analysis core This skill should be used when the user asks to "analyze experimental results", "run strict statistical analysis", "compare model performance", "generate scientific figures", "check significance", "do ablation analysis", or mentions … source
metadata-skills core 24 metadata & bibliometrics skills. Trigger: DOI resolution, citation metrics, author disambiguation, bibliometrics. Design: metadata APIs and bibliometric analysis tools for scholarly records. source
new-project core Full research pipeline from idea to paper. Orchestrates all phases — discovery, strategy, analysis, writing, peer review, and submission. Use when starting a new research project from scratch. source

Source: davila7/claude-code-templates

Skill Tier What it adds Upstream
statistical-analysis core Statistical analysis toolkit. Hypothesis tests (t-test, ANOVA, chi-square), regression, correlation, Bayesian stats, power analysis, assumption checks, APA reporting, for academic research. source
cobrapy core Constraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis. source
exploratory-data-analysis core Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats. This skill should be used when analyzing any scientific data file to understand its structure, content, quality, and characteristics. … source
scientific-critical-thinking core Evaluate research rigor. Assess methodology, experimental design, statistical validity, biases, confounding, evidence quality (GRADE, Cochrane ROB), for critical analysis of scientific claims. source
Excel Analysis core Analyze Excel spreadsheets, create pivot tables, generate charts, and perform data analysis. Use when analyzing Excel files, spreadsheets, tabular data, or .xlsx files. source
anndata core This skill should be used when working with annotated data matrices in Python, particularly for single-cell genomics analysis, managing experimental measurements with metadata, or handling large-scale biological datasets. Use when tasks … source
biomni core Autonomous biomedical AI agent framework for executing complex research tasks across genomics, drug discovery, molecular biology, and clinical analysis. Use this skill when conducting multi-step biomedical research including CRISPR … source
bioservices core Primary Python tool for 40+ bioinformatics services. Preferred for multi-database workflows: UniProt, KEGG, ChEMBL, PubChem, Reactome, QuickGO. Unified API for queries, ID mapping, pathway analysis. For direct REST control, use individual … source
brenda-database core Access BRENDA enzyme database via SOAP API. Retrieve kinetic parameters (Km, kcat), reaction equations, organism data, and substrate-specific enzyme information for biochemical research and metabolic pathway analysis. source
denario core Multiagent AI system for scientific research assistance that automates research workflows from data analysis to publication. This skill should be used when generating research ideas from datasets, developing research methodologies, … source
geniml core This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), building consensus peaks … source
gtars core 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 … source

Source: dotnet/skills

Skill Tier What it adds Upstream
exp-mock-usage-analysis core Audits .NET test mock usage by tracing each mock setup through the production code's execution path to find dead, unreachable, redundant, or replaceable mocks. Use when the user asks to audit mock usage, find unused or unnecessary mock … source

Source: ferdinandobons/startup-skill

Skill Tier What it adds Upstream
startup-design core Design, validate, and plan a startup from scratch. Covers market research, competitive analysis, business model, brand identity, product definition, financial projections, and validation experiments. Trigger when the user has a startup … source

Source: foryourhealth111-pixel/Vibe-Skills

Skill Tier What it adds Upstream
statistical-analysis core Statistical analysis toolkit. Hypothesis tests (t-test, ANOVA, chi-square), regression, correlation, Bayesian stats, power analysis, assumption checks, APA reporting, for academic research. source
designing-experiments core Design experiments and quasi-experiments before analysis. Use when choosing study design, treatment/control structure, outcomes, assumptions, validation plans after scientific experiment failure, or which of DiD, ITS, synthetic control, or … source
exploratory-data-analysis core Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats. This skill should be used when analyzing any scientific data file to understand its structure, content, quality, and characteristics. … source
hypothesis-generation core Structured hypothesis formulation from observations. Use when you have experimental observations or data and need to formulate testable hypotheses with predictions, propose mechanisms, and design experiments to test them. Also owns … source
scientific-critical-thinking core Evaluate scientific claims and evidence quality. Use for assessing experimental design validity, identifying biases and confounders, applying evidence grading frameworks (GRADE, Cochrane Risk of Bias), or teaching critical analysis. Best … source
denario core Multiagent AI system for scientific research assistance that automates research workflows from data analysis to publication. This skill should be used when generating research ideas from datasets, developing research methodologies, … source
geomaster core Comprehensive geospatial science skill covering remote sensing, GIS, spatial analysis, machine learning for earth observation, and 30+ scientific domains. Supports satellite imagery processing (Sentinel, Landsat, MODIS, SAR, … source
scholar-evaluation core Systematically evaluate scholarly work using the ScholarEval framework, providing structured assessment across research quality dimensions including problem formulation, methodology, analysis, and writing with quantitative scoring and … source

Source: HeshamFS/materials-simulation-skills

Skill Tier What it adds Upstream
parameter-optimization core Explore and optimize simulation parameters via design of experiments (DOE), sensitivity analysis, and optimizer selection — generate Latin Hypercube, quasi-random, or factorial sample plans, rank parameter influence with sensitivity … source

Source: hypnguyen1209/offensive-claude

Skill Tier What it adds Upstream
malware-analysis core Use when reverse-engineering or detecting malware — static triage + capa/YARA-X, emulation/DBI/.NET unpacking, dynamic/fileless/Volatility 3 memory analysis, C2 config extraction (Cobalt Strike/CAPE), C2 traffic detection (JA4+, beaconing) source

Source: infrasity-labs/dev-gtm-claude-skills

Skill Tier What it adds Upstream
blog-strategy core Blog strategy development including topic cluster architecture with hub-and-spoke design, audience mapping, competitive landscape analysis, AI citation surface strategy across ChatGPT/Perplexity/AI Overviews, distribution channel planning … source

Source: jeremylongshore/claude-code-plugins-plus-skills

Skill Tier What it adds Upstream
lean-startup core Design MVPs, validated learning experiments, and pivot-or-persevere decisions using Build-Measure-Learn. Use when the user mentions "MVP scope", "validated learning", "pivot or persevere", "vanity metrics", "test assumptions", "innovation … source

Source: K-Dense-AI/claude-scientific-skills

Skill Tier What it adds Upstream
hugging-science core Use when the user is doing AI/ML work in a scientific domain such as biology, chemistry, physics, astronomy, climate, genomics, materials, medicine, ecology, energy, engineering, math, drug discovery, protein design, weather modeling, … source
statistical-analysis core Guided statistical analysis for research data - test selection, assumption checking, effect sizes, power analysis, Bayesian alternatives, and APA-formatted reporting. Use whenever a user wants to compare groups, test a hypothesis, analyze … source
exploratory-data-analysis core Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats. This skill should be used when analyzing any scientific data file to understand its structure, content, quality, and characteristics. … source
hypothesis-generation core Structured hypothesis formulation from observations. Use when you have experimental observations or data and need to formulate testable hypotheses with predictions, propose mechanisms, and design experiments to test them. Follows … source
scientific-critical-thinking core Evaluate scientific claims and evidence quality. Use for assessing experimental design validity, identifying biases and confounders, applying evidence grading frameworks (GRADE, Cochrane Risk of Bias), or teaching critical analysis. Best … source
geomaster core Comprehensive geospatial science skill covering remote sensing, GIS, spatial analysis, machine learning for earth observation, and 30+ scientific domains. Supports satellite imagery processing (Sentinel, Landsat, MODIS, SAR, … source
protocolsio-integration core Integration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and … source
scholar-evaluation core Systematically evaluate scholarly work using the ScholarEval framework, providing structured assessment across research quality dimensions including problem formulation, methodology, analysis, and writing with quantitative scoring and … source

Source: K-Dense-AI/scientific-agent-skills

Skill Tier What it adds Upstream
hugging-science core Use when the user is doing AI/ML work in a scientific domain such as biology, chemistry, physics, astronomy, climate, genomics, materials, medicine, ecology, energy, engineering, math, drug discovery, protein design, weather modeling, … source
statistical-analysis core Guided statistical analysis for research data - test selection, assumption checking, effect sizes, power analysis, Bayesian alternatives, and APA-formatted reporting. Use whenever a user wants to compare groups, test a hypothesis, analyze … source
exploratory-data-analysis core Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats. This skill should be used when analyzing any scientific data file to understand its structure, content, quality, and characteristics. … source
hypothesis-generation core Structured hypothesis formulation from observations. Use when you have experimental observations or data and need to formulate testable hypotheses with predictions, propose mechanisms, and design experiments to test them. Follows … source
scientific-critical-thinking core Evaluate scientific claims and evidence quality. Use for assessing experimental design validity, identifying biases and confounders, applying evidence grading frameworks (GRADE, Cochrane Risk of Bias), or teaching critical analysis. Best … source
geomaster core Comprehensive geospatial science skill covering remote sensing, GIS, spatial analysis, machine learning for earth observation, and 30+ scientific domains. Supports satellite imagery processing (Sentinel, Landsat, MODIS, SAR, … source
protocolsio-integration core Integration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and … source

Source: ljagiello/ctf-skills

Skill Tier What it adds Upstream
ctf-forensics core Provides digital forensics and signal analysis techniques for CTF challenges. Use when analyzing disk images, memory dumps, event logs, network captures, cryptocurrency transactions, steganography, PDF analysis, Windows registry, … source

Source: mohitagw15856/pm-claude-skills

Skill Tier What it adds Upstream
experiment-readout core Analyse a finished A/B test and write an honest results readout with real statistics. Use when asked to read out an A/B test, analyse experiment results, check if a result is statistically significant, or decide ship/no-ship from test … source
ab-test-readout core Analyse a finished A/B test and write the readout — the result, whether it's statistically and practically significant, what it means, and the ship/no-ship call. Use when asked to analyse experiment results, write an A/B test readout, … source

Source: mukul975/Anthropic-Cybersecurity-Skills

Skill Tier What it adds Upstream
detecting-process-injection-techniques core Detects and analyzes process injection techniques used by malware including classic DLL injection, process hollowing, APC injection, thread hijacking, and reflective loading. Uses memory forensics, API monitoring, and behavioral analysis … source
analyzing-macro-malware-in-office-documents core Analyzes malicious VBA macros embedded in Microsoft Office documents (Word, Excel, PowerPoint) to identify download cradles, payload execution, persistence mechanisms, and anti-analysis techniques. Uses olevba, oledump, and VBA … source
analyzing-memory-forensics-with-lime-and-volatility core Performs Linux memory acquisition using LiME (Linux Memory Extractor) kernel module and analysis with Volatility 3 framework. Extracts process lists, network connections, bash history, loaded kernel modules, and injected code from Linux … source
conducting-memory-forensics-with-volatility core Performs memory forensics analysis using Volatility 3 to extract evidence of malware execution, process injection, network connections, and credential theft from RAM dumps captured during incident response. Covers memory acquisition, … source

Source: nexscope-ai/eCommerce-Skills

Skill Tier What it adds Upstream
price-optimization-tool core Evaluate ecommerce price candidates using unit economics, historical observations, elasticity analysis, scenario modeling, and controlled experiments. Use when a seller asks what price to test, how price changes could affect contribution … source

Source: nWave-ai/nWave

Skill Tier What it adds Upstream
nw-interviewing-techniques core Mom Test questioning toolkit, JTBD analysis, interview conduct, assumption testing framework, and hypothesis design source

Source: rampstackco/claude-skills

Skill Tier What it adds Upstream
cro-optimization core Run conversion rate optimization through hypothesis-driven testing including audit, hypothesis generation, test design, statistical analysis, and rollout decisions. Use this skill whenever the user wants to optimize conversion, run A/B … source
experiment-design core A discipline for designing experiments (A/B tests, multivariate, holdouts) so the results actually answer the question you asked. Hypothesis writing, sample size, duration, segment analysis, interpretation, decision-making, and the common … source
data-warehouse-experimentation core Running experiments out of the data warehouse instead of via dedicated experiment platforms. SQL-based assignment, exposure logging discipline, metric definitions in dbt models, statistical analysis in SQL or Python, variance reduction … source

Source: rsmdt/the-startup

Skill Tier What it adds Upstream
requirements-elicitation core Requirement gathering techniques, stakeholder analysis, user story patterns, and specification validation. Use when clarifying vague requirements, resolving conflicting needs, documenting specifications, or validating requirements with … source

Source: wanshuiyin/Auto-claude-code-research-in-sleep

Skill Tier What it adds Upstream
system-profile core Profile a target (script, process, GPU, memory, interconnect) for performance analysis. Use when user says "profile", "benchmark", "bottleneck", or wants performance analysis. source

Source: wondelai/skills

Skill Tier What it adds Upstream
lean-startup core Design MVPs, validated learning experiments, and pivot-or-persevere decisions using Build-Measure-Learn. Use when the user mentions "MVP scope", "validated learning", "pivot or persevere", "vanity metrics", "test assumptions", "innovation … source