Claude Skills by stanfish06

Expert-thinking profile for MEMS Engineer (silicon micromachining / transducer design / simulation & WLT): Reasons from scale-dependent mechanics, squeeze-film damping, and electrostatic pull-in through DRIE Bosch/surface micromachining, CoventorMP/COMSOL, foundry PDKs, LDV/WLI metrology, and AEC-Q103 qual while treating release stiction, DRIE scallop bias, package-stress offset drift, and functional-WLT-vs-reliability...

Two-sample Mendelian Randomisation from GWAS summary statistics with IVW, MR-Egger, weighted median/mode, and

Render Mermaid source locally and preview it in Ghostty, Kitty, or another Kitty-graphics-compatible terminal. Use when a user wants to see a Mermaid diagram without opening a browser; do not use for general image viewing or non-Mermaid diagrams.

Expert-thinking profile for Metabolomics Scientist (wet-lab / LC-MS & GC-MS / computational metabolomics): Reasons from MSI annotation levels, pooled-QC RSD and D-ratio gates, MZmine/MS-DIAL/XCMS pipelines, HMDB/GNPS identification, and MetaboAnalyst batch correction (ComBat, QC-RLSC); treats injection-order drift, ComBat over-correction, and Level-5 pathway stories as first-class failure modes.

Shotgun metagenomics workflow with host-depletion-aware QC, taxonomic profiling, functional profiling, AMR follow-up, and reproducible community output tables.

Expert-thinking profile for Metallurgist (physical / extractive / process metallurgy): Reasons from phase diagrams, TTT/CCT paths, and Scheil solidification through Jominy hardenability (ASTM A255), ASM heat-treat cycles, metallography (ASTM E3/E112/E407), and staged failure analysis while treating decarburization, quench cracking, HAZ liquation, hot tearing, and microsegregation as first-class failure...

Expert-thinking profile for Meteorologist (operational / research atmospheric forecasting): Reasons from hydrostatic and geostrophic balance, scale-dependent dynamics, and the obs-to-NWP pipeline; works the Snellman funnel, matches HRRR/GFS/ECMWF to scale, and treats spin-up, convective scheme bias, radar AP, and PoP misinterpretation as first-class failure modes.

Compute epigenetic age from DNA methylation arrays using PyAging clocks from GEO accessions or local files.

Design custom metric packs for plugin-eval so teams can add local evaluation rubrics that emit schema-compatible checks and metrics. Use when the user wants their own evaluation criteria or visualizations.

Expert-thinking profile for Metrology Scientist (calibration laboratory / NMI / measurement assurance): Reason from SI traceability, GUM uncertainty budgets, and VIM distinctions between calibration and verification; propagates Type A/B components, CIPM MRA equivalence, and ILAC decision rules before any pass/fail claim.

Expert-thinking profile for Microbial Ecologist (field / mesocosm / amplicon & metagenomic community ecology): Reasons from Vellend assembly (selection, dispersal, drift, diversification), compositional stats (ANCOM-BC2, MaAsLin2, Aitchison), and SILVA/GTDB/EMP workflows; treats kitome contamination, GCN bias, pseudoreplication, SparCC-as-interaction, and PICRUSt2-as-measured-function as first-class failure modes.

Expert-thinking profile for Microbial Physiologist (wet-lab / chemostat & metabolic- flux physiology): Reasons from Monod/chemostat (μ = D), YX/S and Pirt maintenance, Crabtree/overflow, 13C-MFA and FBA, and BMSAB taxonomy; treats OD-as-biomass yield error, FBA-as-measured-flux, washout misread, and portable ms across media as first- class failure modes.

Expert-thinking profile for Microbiologist (wet-lab / culture, amplicon & shotgun microbiomics): Reasons from culturability limits, CFU/MPN enumeration, selective media, DADA2/QIIME2 16S ASVs (SILVA/GTDB), and shotgun metagenomics (Kraken2, MetaPhlAn, HUMAnN); treats plate-count anomaly, compositional stats pitfalls, kit contamination, and index hopping as first-class failure modes.

Expert-thinking profile for Microbiome Scientist (cohort / intervention / multi-omics host–microbiome): Reasons from compositional and longitudinal stats (MaAsLin2, ANCOM- BC2), STORMS pre-analytics, FMT/LBP and diet trials, and multi-omics integration; treats PPI/antibiotic confounders, kitome contamination, host-DNA swamping, and HMA causality overclaim as first-class failure modes.

Expert-thinking profile for Microelectronics Engineer (packaging / assembly / thermal & reliability): Reasons from CTE mismatch, θja networks (JESD51), and package RLC through wire bond (Au–Al IMC, loop height), flip-chip (UBM, underfill, HIP/NWO), J-STD-020 MSL, and JESD22 TCT/uHAST; treats datasheet θja without board definition, wire sweep, die-attach voids, and soak-mode mismatch as first-class failure modes.

Migrate a .NET 10 project or solution to .NET 11 and resolve all breaking changes. This is a MIGRATION skill — use it when upgrading from .NET 10 to .NET 11, NOT for writing new programs. USE FOR: upgrading TargetFramework from net10.0 to net11.0, fixing build errors after updating the .NET 11 SDK, resolving source-breaking and behavioral changes in .NET 11 runtime, C# 15 compiler, and EF Core 11, adapting to updated minimum hardware requirements (x86-64-v2, Arm64 LSE), and updating CI/CD pip...

Migrate a .NET Framework (4.x) project or solution to modern .NET (10), the large cross-runtime jump — not a version bump. USE FOR: ".NET Framework migration", "netfx to net", porting net48/net472 to net10.0 (or net8.0/net9.0), assessment with the .NET Upgrade Assistant / GitHub Copilot app modernization ("modernize .NET") / apiport, converting old-style .csproj to SDK-style, "packages.config" → <PackageReference>, replacing System.Configuration, "WCF migration" to CoreWCF or gRPC, porting Sy...

Migrate MSTest v1 or v2 test projects to MSTest v3. Use when the user asks to upgrade MSTest and the project has QualityTools assembly references, MSTest.TestFramework/TestAdapter 1.x-2.x, .testsettings, or migration errors after changing those packages to 3.x. USE FOR: upgrading from MSTest v1 assembly references (Microsoft.VisualStudio.QualityTools.UnitTestFramework) or MSTest v2 NuGet (MSTest.TestFramework 1.x-2.x) to MSTest v3, fixing assertion overload errors (AreEqual/AreNotEqual), upda...

Replace existing static dependency call sites with a wrapper or built-in abstraction that already exists or is registered in DI. Codemod-style bulk replacement of DateTime.Now/UtcNow to TimeProvider, File.ReadAllText to IFileSystem, and similar, across a bounded scope (file, project, namespace), adding constructor injection to affected classes and updating their unit tests to use a test double. USE FOR: replace DateTime.UtcNow/DateTime.Now with TimeProvider and add the constructor parameter, ...

Migrates .NET test projects from VSTest to Microsoft.Testing.Platform (MTP). Use when user asks to "migrate to MTP", "switch from VSTest", "enable Microsoft.Testing.Platform", "use MTP runner", set OutputType=Exe only for test projects in Directory.Build.props, or mentions EnableMSTestRunner, EnableNUnitRunner, or UseMicrosoftTestingPlatformRunner. USE FOR: MTP behavioral differences vs VSTest (exit code 8, zero tests discovered, --ignore-exit-code, TESTINGPLATFORM_EXITCODE_IGNORE); centraliz...

Convert .NET test projects from xUnit.net v2 or v3 to MSTest v4. Use for replacing xunit packages, [Fact]/[Theory], xUnit assertions, fixtures, ITestOutputHelper, traits, skips, and xUnit parallelization with MSTest equivalents while preserving the current VSTest or MTP runner. DO NOT USE FOR: xUnit v2 to v3 upgrades, MSTest version upgrades, migrations from NUnit/TUnit, or runner-only VSTest to MTP migrations.

Use when a user needs help triaging dbt-core to Fusion migration errors. Runs dbt-autofix first, then classifies remaining errors into actionable categories (auto-fixable, guided fixes, needs input, blocked).

Use when migrating a dbt project from one data platform or data warehouse to another (e.g., Snowflake to Databricks, Databricks to Snowflake) using dbt Fusion's real-time compilation to identify and fix SQL dialect differences.

Stand up Grafana Mimir for horizontally scalable, multi-tenant, long-term Prometheus + OTLP metrics storage. Covers monolithic / read-write / microservices deployment, S3 / GCS / Azure / filesystem block storage, Prometheus `remote_write` and OTLP ingestion, multi-tenancy with `X-Scope-OrgID`, ingester replication factor, compactor retention, and per-tenant limits. Use when running Mimir locally or on Kubernetes (Helm `mimir-distributed`), scaling Prometheus past a single node, picking ingest...

Expert-thinking profile for Mineralogist (laboratory / field mineral identification / crystallography / economic mineralogy): Reasons from crystal chemistry, Pauling coordination, and converging optics–XRD/Raman–EPMA evidence; uses RRUFF/Mindat/AMCSD and CNMNC Checklist 2025 while treating preferred orientation, clay EG/heat triads, metamict amorphization, and QEMSCAN library bias as first-class failure modes.

Expert-thinking profile for Mining Geologist (field / exploration drilling / ore deposit modelling / geostatistics / resource estimation): Reasons from deposit-type models (porphyry, VMS, SEDEX, orogenic Au, IOCG, skarn) through oriented core logging, domaining, variography, OK/MIK/LUC estimation, and Chain-of-Mining reconciliation to JORC Table 1, NI 43-101 Item 14, and CIM MRMR reporting; uses Leapfrog, GIM Suite/MX Deposit, and Parker F-series factors...

Manage Mixpanel Headless authentication: check session state, list/add/use accounts, run OAuth login, switch projects/workspaces, manage targets, and check bridge credentials.

This skill installs mixpanel_headless, pandas, numpy, matplotlib, seaborn, networkx, anytree, scipy (and pyarrow on Python 3.11+), then verifies Mixpanel credentials. Use when setting up a new environment for Mixpanel data analysis, when dependencies are missing, or when configuring service account or OAuth credentials for the first time.

Use when the user asks about Mixpanel product analytics, event data, funnel analysis, retention curves, cohort analysis, segmentation queries, user behavior, conversion rates, churn, DAU/MAU, ARPU, revenue metrics, feature adoption, A/B test results, user paths, flow analysis, or any request to query, explore, visualize, or analyze Mixpanel data using Python. Also use when the user asks to read, write, or manage Mixpanel \"business context\" — the markdown documentation that grounds AI assist...

Onboards users to MLflow by determining their use case (GenAI agents/apps or traditional ML/deep learning) and guiding them through relevant quickstart tutorials and initial integration. If an experiment ID is available, it should be supplied as input to help determine the use case. Use when the user asks to get started with MLflow, set up tracking, add observability, or integrate MLflow into their project. Triggers on "get started with MLflow", "set up MLflow", "onboard to MLflow", "add MLfl...

Expert-thinking profile for MLOps Engineer (ML lifecycle ops / feature stores & serving / drift monitoring / CI-CD-CT / registry promotion): Reasons from data contracts, feature parity, evaluation gates, and rollback-readiness through MLflow/W&B registries, Feast feature stores, KServe/Triton serving, Great Expectations/TFDV validation, and Evidently PSI/KS drift monitors while treating train-serve skew, data leakage, silent degradation, and schema/concept...

Use for authorized Android or iOS application reverse engineering and security testing, including APK or IPA analysis, runtime instrumentation, SSL pinning, and platform protection checks.

Modal is a serverless cloud platform for running Python on demand, including on-demand GPUs. Use when deploying or serving AI/ML models, running GPU-accelerated workloads (training, fine-tuning, inference), serving web endpoints, scheduling batch jobs, or scaling Python code to cloud containers with the Modal SDK.

Modern TypeScript 5.x idioms — strict tsconfig (strict, noUncheckedIndexedAccess), the type system (unions/intersections, generics + constraints, narrowing, discriminated unions, unknown vs any, utility types, satisfies, as const, template-literal types), ESM & moduleResolution, and type-safe patterns (branded types, exhaustiveness). Use when configuring a tsconfig, writing or reviewing type-safe TypeScript, designing generics or a discriminated union, or decoding a tsc error.

Multi-Omics Factor Analysis v2 (MOFA+) with mofapy2. Jointly decompose omics layers (scRNA, ATAC, proteomics, methylation) into latent factors capturing major variation. Multi-group designs. AnnData views → MOFA object → train → variance explained → correlate factors with metadata → visualize/cluster → enrich top loadings.

Expert-thinking profile for Molecular Biologist (wet-lab / molecular genetics / functional genomics / assay validation (MIQE, ARRIVE 2.0)): Reasons from central-dogma sequence flow, binding affinity (Kd/Km/kcat), gene regulation, and biological-versus- technical replicate structure through MIQE-compliant RT-qPCR, ddPCR, Western/flow/microscopy, CRISPR editing with rescue, and IWGAV antibody validation while treating off-target reagent effects, batch...

Use when running classical protein-ligand docking with AutoDock Vina, smina, or GNINA, including receptor or ligand preparation, search-box setup, docking, pose analysis, virtual screening, affinity scoring, or GNINA rescoring of DiffDock poses. Trigger terms include docking, PDBQT, binding pose, and protein-ligand.

Expert-thinking profile for Molecular Ecologist (field / lab / computational population & environmental genetics): Reasons from population genetics, eDNA/metabarcoding, and marker choice (microsatellites, SNPs, mtDNA); analyzes with STRUCTURE/ADMIXTURE, hierfstat FST, DADA2 pipelines, and ddPCR; treats null alleles, Wahlund effect, batch effects, and eDNA allelic dropout as first-class failure modes.

Expert-thinking profile for Molecular Geneticist (clinical / research): Reasons from sequence-as-hypothesis, reference context (genome build, MANE/RefSeq transcript, HGVS), and allele-level molecular consequence through ACMG/AMP-ClinGen criteria, IGV/VEP/SpliceAI/gnomAD/ClinVar review, MIQE-compliant qPCR/ddPCR, and Sanger/NGS validation while treating allele dropout, pseudogene/paralog...

Expert-thinking profile for Molecular Neuroscientist (wet-lab / synaptic biochemistry + optogenetics + viral tracing + region RNA-seq): Reasons from NPQ transmission, AMPAR/NMDAR trafficking, monoamine receptor/transporter systems, optogenetics (ChR2/Chrimson/ACR) with retinal-artifact controls, AAV/rabies circuit tracing, and region RNA-seq with DESeq2/SynGO—integrating synaptic biochemistry, perturbation, and omics while treating mini-detection...

Expert-thinking profile for Molecular Pathologist (clinical / anatomic & molecular diagnostic pathology): Reasons from tumor cellularity, assay-specific LOD, and AMP/ASCO/CAP Tier I–IV classification; validates IHC (CAP ≥90% concordance), FISH (HER2/ALK break-apart), and NGS oncology panels under CAP/CLIA MM09 while treating FFPE deamination, HER2-low/ultralow scoring, PD-L1 TPS vs CPS, and ctDNA CHIP as first-class...

Expert-thinking profile for Molecular Virologist (wet-lab / reverse genetics & virus–host molecular mechanism): Reasons from Baltimore mRNA pathways, RNP/polymerase biochemistry, cap-snatching and expression strategy, CPER/BAC/trVLP rescue, protease cis/trans mapping, viral-factory LLPS, and CRISPR host-factor screens (Brunello/MAGeCK/replicon/TRPPC) with iCLIP/ChIP-seq—while treating CPER PCR errors, DIP packaging competition...

Molecular featurization for ML (100+ featurizers). ECFP, MACCS, descriptors, pretrained models (ChemBERTa), convert SMILES to features, for QSAR and molecular ML.

Use this skill for MolMIM, NVIDIA's BioNeMo NIM microservice for small-molecule latent-space generation and optimization. Invoke for MolMIM, molecular embeddings, hidden states, latent decoding, sampling around a seed SMILES, CMA-ES guided molecule generation, QED or plogP optimization, hosted NVIDIA API calls, or local Docker deployment.

Medical imaging deep learning with MONAI, PyTorch, pydicom, pathml, histolab, and napari-viz. Use for segmentation, classification, registration, transforms, sliding-window inference, NIfTI/DICOM workflows, medical image datasets, and reproducible clinical imaging AI pipelines.

Use when the user asks for Moody's company profiles, ownership, ratings, credit opinions, financial statements, filings, peers, research, or credit-risk analysis for a company.

Produce an Earnings Call Summary HTML report for 2–5 companies using Moody's GenAI MCP tools. Use this skill whenever the user asks to summarize earnings calls, generate an earnings call summary, analyze earnings transcripts across peers, or create an earnings call report. Trigger even if they just name companies and mention "earnings" or "transcript".

Discover and safely explore Moody's MCP tools. Use when the user wants to see what Moody's data is available, verify MCP connectivity, look up an entity, or run a lightweight ratings/research probe before deeper analysis.

Produce a comprehensive Issuer Brief HTML report for a company using Moody's GenAI MCP tools. Use this skill whenever the user asks to create an Issuer Brief, company profile report, credit memo, investment book, or comprehensive company analysis. Also trigger when they ask for a report combining company overview, financials, peer comparison, industry overview, strategic developments, management, credit profile, risks, and ESG into a single document. Trigger even if they just name a company a...

Produce a Peer Analysis HTML report for a target company and its credit peers using Moody's GenAI MCP tools. Use this skill whenever the user asks to compare a company against its peers, run a peer analysis, do a credit peer comparison, generate a peer group report, or analyze relative credit positioning. Trigger even if they just name a company and mention "peers", "peer comparison", "credit comparison", "peer group", or "relative value".